Physiological Effects of Feeding

Chapter 13

Physiological Effects of Feeding

Chris Carter, Dominic Houlihan, Anders Kiessling, Francoise Médale and Malcolm Jobling

13.1 Introduction

Physiology is the study of how animals function. When we think of physiology in fi sh, the experiments that usually spring to mind involve analysis of tissues or blood, the fl ow of sub-stances in or out of the animal, or the ways in which particular fi sh species seem to be adapted to their environment. Measurements may be based on individuals or groups of fi sh. A char-acteristic feature of physiological measurements in fi sh has been the use of unfed animals, i.e. in a postabsorptive state (Schreck & Moyle 1990). This is usually done in an attempt to reduce the variability that exists within a group of fi sh held under normal feeding and rearing conditions. Thus, we know quite a lot about the physiology of unfed fi sh, but relatively little about the physiology of fi sh whose food intake has been carefully measured before experi-ments have been started.

Exceptions to this generalisation are the studies on bioenergetics and the physiological changes following a single meal (see reviews by Brett 1979, 1995; Brett & Groves 1979; El-liott 1979; Cho et al. 1982; Schreck & Moyle 1990; Jobling 1993, 1994, 1997) and on food processing (Fänge & Grove 1979; Grove 1986). In such studies, individuals or groups of fi sh have been fed a known amount of food, and measurements such as oxygen consumption made (e.g. Solomon & Brafi eld 1972; Beamish 1974). It has long been recognised that feed-ing introduces a dynamic into individual physiological systems as the animals deal with the consequences of the meal. Fish nutrition is a particular branch of physiology that has largely been concerned with establishing relationships between ration and growth, comparisons be-tween feed ingredients and the determination of nutritional requirements. In the latter, em-phasis has been on feed composition and assessment of mean response. The quantity of food eaten by the fi sh has usually not been measured, and this has resulted in requirements being expressed as a relative proportion or percentage of the diet (e.g. NRC 1993). Several books and monographs are available that provide discussions of feed composition and nutritional requirements (Halver 1972, 1989; Cowey 1982; Cowey et al. 1985; Wilson 1991; Higgs etal. 1995; see also Chapters 2 and 11).

The focus of this chapter is on studies where food intake has been measured and related to physiological effects. By pointing to the studies where food intake has been measured, we aim to demonstrate that in such cases there is a marked improvement in the interpretation of the results. In particular, we have highlighted the effects of the quantifi cation of protein intake

Food Intake in Fish Edited by Dominic Houlihan, Thierry Boujard, Malcolm Jobling

Copyright © 2001 by Blackwell Science Ltd

298 Food Intake in Fish

on amino acid metabolism, working from the rationale that growth has a close relationship with protein accretion.

13.2 Different methods of feeding

The physiological responses to feeding in fi sh are dependent upon the amount of food eaten. If the physiological question that is being posed demands that the amount of food being consumed is known, a method for the measurement of food intake must be incorporated into the experimental design (see Chapter 3). Decisions must also be made concerning the use of single or groups of fi sh. Food intake of single fi sh or of individuals in a small group may be measured over the duration of an experiment, but the monitoring of uptake by individu-als within larger groups is problematic. The measurement of food intake of fi sh using hand-feeding techniques is extremely time-consuming, and this places limits on the number of treatments and replicates. Hand-feeding can, however, yield accurate information for relat-ing food intake to physiological effects (Elliott 1976; Houlihan et al. 1989; Lyndon et al.1992). Observations (direct or from a video recording) made on an individual’s food intake (see Chapter 3) can be related to physiological effects measured at a later time. This approach has often formed the basis for the study of energy and nitrogen budgets because it allows investigation of relationships between known food intake and measures of metabolic physiol-ogy and growth (e.g. Solomon & Brafi eld 1972; Cui & Wootton 1988; Carter & Brafi eld 1991). The measurement of day-to-day variation in food intake is also possible, but only relatively few studies have related individual patterns (day-to-day variation) of food intake to a physiological response (Rozin & Mayer 1961; Jobling & Baardvik 1994; Ali et al. 1998; Shelverton & Carter 1998).

Manual or automatic feeding may be used for larger groups of fi sh and the food intake of individual animals determined by X-radiography (Talbot & Higgins 1983; see Chapter 3). This approach has been used to relate food intake to a variety of physiological effects, particularly in relation to the performance of individual fi sh within groups (see reviews by Jobling et al. 1990, 1995; McCarthy et al. 1993; Carter et al. 1995b; see also Chapter 3). There are several approaches to measuring food intake by groups of fi sh via combining dif-ferent methods of delivery (e.g. manual feeding, automatic feeders, demand feeders) with assessment of uneaten food (e.g. collection of uneaten food from the tank outfl ow or use of hydroacoustic transducers; see Chapter 3). Such methods relate to physiological effects in different ways and do not allow investigation of physiological effects at the level of the individual. The collection of uneaten food allows the calculation of food intake and this, in turn, enables assessment of utilisation effi ciencies to be made (see Chapter 1).

For all of these methods, long-term (long enough for measurable growth to occur) physi-ological effects depend on measuring or predicting total food intake over weeks. Also fi sh should be subject to a stable nutritional regime (fed the same amount in the same way each day), and if terminal measurements are to be made the nutritional regime used on the fi nal day should refl ect the normal regime. In the following account, short-term (within 24·hours)physiological effects relate to the food intake from the meal immediately preceding the meas-urements.

Physiological Effects of Feeding 299

13.3 Short-term effects of a meal

Fish on a stable nutritional regime exhibit repeatable physiological events that cycle over 24·hours. Daily growth cannot easily be measured, but is the result of the links between these cycles and food intake on, for example, oxygen consumption, nitrogenous excretion and protein metabolism. In studies in which care has been taken to isolate the effects of food intake from time of feeding it has been shown that a given ration may be used differently when consumed at different times of the day (Boujard et al. 1995; Gelineau et al. 1998; Verbeeten et al. 1999; see Chapter 10).

The main purpose of this section is to detail short-term physiological effects of feeding in order to provide a link to long-term growth. Food processing by the gastrointestinal tract (GIT) may have major effects on both the absorption of nutrients and on food intake (Fänge & Grove 1979; Grove 1986; Holmgren et al. 1986). Investigation of food processing has usually been focused on relating major parameters (species, fi sh size, temperature) and variations in meal size, meal frequency and the composition of the meal to gastrointestinal emptying (for reviews see Fänge & Grove 1979; Jobling 1986, 1987; dos Santos & Jobling 1991; Bromley 1994). The overriding impression is of fl exibility in patterns of emptying (for a selected spe-cies) depending on the characteristics of the feeding regime and of the food (Grove 1986; Jobling 1986, 1987; dos Santos & Jobling 1991). For example, Fletcher et al. (1984) showed that when two meals were fed to dab (Limanda limanda) 3·h apart, the inclusion of a binder in the feed meant that the two meals did not mix in the stomach. Without the binder, the two meals became mixed in the stomach and this slowed evacuation. Such studies provide ways of predicting the rate of gastrointestinal emptying and, in turn, the rate of appetite return (Grove et al. 1978). Regulation of the GIT at a pharmacological level is extremely complex, and few detailed descriptions are available (see Fänge & Grove 1979; Holmgren et al. 1986; Chapter 12). However, it is thought that the physical and chemical (nutritional) characteristics of the feed will have short-term effects on satiety through responses elicited in the GIT via chemo- and mechanoreceptors (Fletcher 1984).

A large part of the increase in oxygen consumption that follows the ingestion of a meal (Heat Increment of Feeding, HIF) is thought to be due to amino acid fl uxes and the turnover of protein (Jobling 1981, 1993; Houlihan et al. 1988; Houlihan 1991). The balance between protein and energy utilisation is obviously central to growth. Associated with the rise in oxy-gen consumption following a meal is an increase in ammonia production from the oxidation of amino acids. The working hypothesis is that the fl ow of ingested amino acids to the tissues causes an increase in both amino acid oxidation and protein synthesis, but there is no single study that tests this hypothesis. Thus, data from different experiments need to be combined to elaborate the relative changes in short-term physiological effects that occur over the 24·hfollowing feeding (Fig. 13.1). Protein synthesis increases by the largest relative amount and appears to show two peaks, the fi rst at 6·h and a larger peak at 18·h (Fig. 13.1). Part of the explanation for this may be that tissues have different temporal patterns of protein synthesis; for example, liver protein synthesis activity tends to peak before that of white muscle (Lyndon et al. 1992). There are smaller relative increases in both oxygen consumption (Lyndon etal. 1992) and ammonia excretion (Ramnarine et al. 1987), but these are not synchronised (c.f. Fig. 13.4). These two experiments provide a useful comparison (data selected for simi-larity in protein intake, fi sh weight and temperature) and raise questions about the degree


of synchronisation between physiological effects. They also highlight a direction for future research.

13.4 Tissue metabolic physiology

Amino acid fl ux and temporal changes in free amino acid concentrations in different tissues highlight the dynamic relationships between protein intake, tissue metabolism and the utili-sation of amino acids for protein synthesis. An ability to regulate a large infl ux of amino acids, presumably to maintain tissue homeostasis as well as to optimise the utilisation of dietary protein and energy, is central to these relationships. Feeding results in an infl ux of dietary amino acids that is usually greater than the total amount of free amino acids in the whole fi sh (Carter et al. 1995a; Houlihan et al. 1995a). It is therefore not unexpected that tissue free amino acid concentrations change following feeding. Changes are sequential between tis-sues and, to some extent, refl ect a route through the tissues concerned with digestion, absorp-tion, metabolism and then growth. However, these changes appear relatively small (Walton & Wilson 1986; Espe et al. 1993; Lyndon et al. 1993; Carter et al. 1995a), especially when seen in relation to relative changes in events such as protein synthesis (Fig. 13.2). This sup-ports the hypothesis that protein synthesis has a key role in the regulation of free amino acid concentrations.

The liver has a central role in amino acid metabolism and in the regulation of amino acid transport to ‘downstream’ tissues. Its free amino acid pool concentration is infl uenced by the import and export of amino acids as free amino acids, peptides or proteins as well as by the use of amino acids within the tissue (Jürss & Bastrop 1995). There is, therefore, a link between cycles of protein turnover, free amino acid fl uxes and nitrogenous excretion. In the livers of unfed salmonids total free amino acid concentrations are typically between 30 and 50·μmol/g,

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Fig. 13.1 Short-term effects (% of 0-h values) of food intake on protein synthesis and oxygen consumption (Lyn-don et al. 1992), and on ammonia excretion (Ramnarine et al. 1987) in Atlantic cod.


with essential amino acids (EAAs) accounting for from 10 to 15% of the total (Walton & Wilson 1986; Médale et al. 1987; Carter et al. 1995a). Total free amino acid concentrations increase over a few hours following feeding (Walton & Wilson 1986; Carter et al. 1995a), and EAA show the largest peaks. Thus, it could be hypothesised that EAAs are not metabolised as rapidly as the non-essential amino acids (Walton & Wilson 1986). One additional feature may be differences in patterns shown by specifi c EAAs. Arginine, phenylalanine and threo-nine concentrations peak fi rst, and a second peak was due to valine, isoleucine, leucine and methionine, although the latter amino acids may also have increased during the fi rst peak (Walton & Wilson 1986). This pattern implies an initial response to dietary amino acids, and a second peak that may have been related to increases in endogenous amino acid metabo-lism and rates of protein synthesis (Lyndon et al. 1992). RNA concentration expressed as the capacity for protein synthesis (mg RNA per g protein; Sugden & Fuller 1991) remains relatively stable (McMillan & Houlihan 1992), which suggests that most of the increased protein synthesis in the liver is due to an increase in ribosomal activity (Fig. 13.2). These studies refer to the effects induced by a single meal, following several days without food; comparable studies on fi sh fed daily would be of great interest.

Free amino acid pools in white muscle are relatively unaffected by feeding (Fig. 13.3) (Ogata 1986; Espe et al. 1993; Lyndon et al. 1993; Carter et al. 1995a), although there are some differences between studies that are not readily explained. Before feeding, total free amino acid pool concentrations in the white muscle in salmonids are around 30·μmol/g, with EAAs accounting for 20% of the total (Medale et al. 1987; Espe et al. 1993; Carter et al.1995a). Following feeding, concentrations rarely exceed 150% of the pre-feeding levels, and the proportion of EAAs does not change signifi cantly (Kaushik & Luquet 1977; Espe et al.1993; Carter et al. 1995a). As in the liver, there is considerable variation in the time course of the changes in different EAAs. It is also diffi cult to fi nd consistent trends among the results

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Fig. 13.2 Short-term effects (% of 0-h values) of food intake on free amino acid pool concentrations (Carter et al.1995a), rates of tissue protein synthesis and the capacity for protein synthesis (RNA:protein) (McMillan & Houlihan 1992) in the liver of rainbow trout following feeding at 0 h.


from different studies. However, although there are differences between individual amino acids, the total free amino acid pool concentrations and composition show considerable sta-bility and there is, presumably, some form of regulation (Lyndon et al. 1993; Carter et al.1995a; Houlihan et al. 1995a,b).

Attempts have been made to relate amino acid profi les in tissues, particularly the blood, to the amino acid composition of the diet (Nose 1972; Walton & Wilson 1986). If food intake is measured, then quantifi cation of the amount of amino acid consumed is possible. Amino acid intake was found to correlate with the total and EAA free pool concentrations in the pylorus 4·h following feeding, illustrating the rapid uptake of dietary amino acids into this tis-sue (Carter et al. 1995a). There were few signifi cant correlations between amino acid intake and amino acids in the liver or white muscle free pools (Walton & Wilson 1986; Lyndon et al.1993; Carter et al. 1995a). This is not surprising given the large number of factors involved in regulating the concentration and composition of the tissue free amino acid pools (Fuller & Garlick 1994; Arzel et al. 1995). Recently, the importance of the gastrointestinal tract in metabolising amino acids derived from recycling (rather than the food) has been recognised in mammals (Reeds et al. 1999), and this may also be of signifi cance in fi sh.

We know less about tissue concentrations of other metabolites or metabolic enzyme activi-ties (see p. 309, Biochemical correlates of food intake). The data on diurnal variations of liver glycogen content do not demonstrate a defi nite effect of food intake, and the delay between mealtime and the highest liver glycogen concentrations varies with season and the age of the fi sh (Delahunty et al. 1978; Laidley & Leatherland 1988). The time-course of the appear-ance of plasma glucose (and of other simple sugars) following feeding will depend on dietary factors, such as total carbohydrate content, feed ingredients and their processing, as well as on the species (feeding habits and trophic niche), water temperature and nutritional his-tory (Bergot & Breque 1983; Hung 1991). Omnivorous and herbivorous species utilise diets

Fig. 13.3 Short-term effects (% of 0-h values) of food intake on free amino acid pools in the white muscle for rainbow trout (RT) and Atlantic salmon (AS) following feeding at 0 h. (Espe et al. 1993; Carter et al. 1995a, 2000).


containing higher carbohydrate contents than do carnivorous species, but some carnivorous fi sh are able to adapt to dietary carbohydrate (Wilson 1994).

Ingestion of a diet containing relatively high levels of digestible carbohydrate and lipid leads to an increase in plasma glucose and triacylglycerol concentrations in rainbow trout (Oncorhynchus mykiss) (Brauge et al. 1994, 1995). The arrival of such nutrients in the plasma generally occurs within 2·h after feeding (Brauge et al. 1994; Medale et al. 1999). Higher temperatures speed up the appearance of digestion products in the plasma (Brauge et al.1995), presumably due to an increase in digestion and absorption rates. Consequently, in ad-dition to diet composition, the profi le of plasma metabolite concentrations mainly depends upon water temperature that also affects energy demands. The magnitude of the plasma glu-cose increase following a meal is infl uenced by the amount of digestible carbohydrates sup-plied by the diet (Brauge et al. 1994; Hemre et al. 1995). Increasing dietary wheat starch was positively correlated with plasma glucose, but negatively correlated with plasma triacylglyc-erols in Atlantic salmon (Salmo salar) (Hemre et al. 1995). A wide range of dietary lipid (31 to 47%) had no effect on plasma triacylglycerol concentration. When the highest dietary levels of lipid were combined with the lowest carbohydrate levels, the result was the highest plasma glucose levels; these may have been due to unknown stresses associated with the very high level of fat (Hemre & Sandnes 1999). Such studies emphasise the importance of measuring food intake, and point to problems in interpreting the effects of dietary manipulation when more than one variable is changed.

Insulin secretion, which acts on amino acid and glucose regulation, appears to be driven by food intake (Plisetskaya et al. 1991; Rungruangsak-Torrissen et al. 1999). Individual food intake was positively correlated with plasma insulin and growth rate in Atlantic salmon (Rungruangsak-Torrissen et al. 1999), and the links to feeding may partly explain the correla-tions between plasma insulin, body weight and growth rate found in an earlier study (Pliset-skaya et al. 1991). Plasma glucose concentrations do not seem to provide an index of glucose utilisation (Wilson 1994). Fish, especially carnivores, are best able to utilise carbohydrate when rates of absorption and appearance in the blood are low (Meton et al. 1999).

Generally, body lipid refl ects dietary lipid both in terms of amount and fatty acid composi-tion (see Chapter 15). As food intake increases, so does lipid deposition, and the infl uence of the phospholipid fatty acid fraction associated primarily with the cell membranes becomes less (Pickova 1997). Lipids can also be synthesised from carbohydrates and amino acids. When the effects of feeding time are separated from the amount of food consumed it has been demonstrated that there is a depressive effect of feeding time on non-esterifi ed fatty acids (NEFA) concentrations in plasma (Boujard & Leatherland 1992). These results are consistent with data obtained from rats and humans where plasma NEFA levels produced by lipolysis are inversely correlated with time after food intake (Aschoff 1979).

13.5 Whole-animal metabolic physiology

13.5.1 Respiration and excretion

The rate of oxygen consumption increases after feeding in fi sh. Usually, there is a peak in oxygen consumption two to three times above the pre-feeding level within a few hours after


the end of the meal; the metabolic rate then declines to the pre-feeding level. Linear relation-ships between feed intake and HIF have been established (Jobling 1981, 1985; Carter & Brafi eld 1992). Carter and Brafi eld (1992) measured daily food intake and the associated HIF of individual grass carp (Ctenopharyngodon idella) held in respirometers for 20–30 days. They found that, depending on feed composition, HIF increased between 12.7 and 18.5·mgO

2/g per day for each kJ of energy absorbed. Patterns of ammonia and carbon dioxide excre-

tion have also been measured. These have been linked to food intake, diet composition and the utilisation of metabolic substrates through the calculation of respiratory and ammonia (nitrogen) quotients (Brafi eld 1985; Gelineau et al. 1998; Owen et al. 1998; Médale et al.1999). There appears to be synchronisation between postprandial increases in metabolism of common carp (Cyprinus carpio) measured in these ways (Fig. 13.4), but relative differences between the pathways may reveal changes in the balance between the use of substrates for aerobic respiration. In some cases the physiological responses to feeding have been observed to return to pre-feeding levels within 24·h (e.g. Owen et al. 1998; Médale et al. 1999), but responses may be longer-lasting in fi sh such as in Atlantic cod (Gadus morhua), that take over 24·h to process a meal (e.g. Saunders 1963; Ramnarine et al. 1987). The duration of the various physiological responses to a meal may be expected to depend upon such factors as the size of the meal, the ease with which it is digested, its nutrient composition and temperature (Jobling 1981).

The design of the respirometer chamber used in such studies may affect the results ob-tained due to infl uences on the behaviour and physiology of the fi sh. Oxygen consumption is often high for as long as 24·h after a fi sh is introduced into a respirometer, so there needs to be an adequate period of acclimatisation before the recording of metabolic rates. Other problems relate to establishing the feeding regime. One approach is to hold animals individually in a respirometer for several days, or longer (e.g. Solomon & Brafi eld 1972; Carter & Brafi eld

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Fig. 13.4 Short-term effects (% of 0-h values) of oxygen consumption, carbon dioxide excretion and ammonia excretion for common carp following feeding at 0 and 7 h (fed 1.5% body weight distributed as two equal rations). (Adapted from Médale et al. 1999.)


1991). In such experiments feeding behaviour can be observed, the amount of food consumed can be measured, and consumption can then be related to metabolic responses and growth. An advantage when working with individuals is that behaviour can be recorded and, if it appears abnormal, then the results can be excluded. Under such circumstances increases in oxygen consumption can be ascribed to the effects of the meal and not confounded with increases in activity. Experiments may also be carried out on groups of fi sh where the amount of food consumed by the group is determined, and the oxygen consumption and other metabolic parameters of the animals recorded (Heinsbroek et al. 1993; Owen et al. 1998).

The quantity (absolute and relative to other macronutrients) and quality (amino acid com-position) of absorbed protein will infl uence the HIF, rates of protein synthesis, ammonia pro-duction and the relationships between them. Analysis of diurnal cycles in amino acid metabo-lism suggest that the surge in protein synthesis following feeding occurs at approximately the same time as the oxidation of amino acids and the excretion of ammonia (P. Campbell etal. unpublished data). A link between the postprandial profi les of ammonia excretion and the amount of food fed has been found in rainbow trout (Médale et al. 1995). The time-course of protein breakdown is not known, but may be of considerable importance (Millward & Rivers 1988). For example, it is possible that, depending upon the size of the meal and the speed of digestion, protein accretion may be controlled by the rapidity of the rise and fall not only of protein synthesis but also protein breakdown.

13.5.2 Protein turnover

Stimulation of protein synthesis following feeding (McMillan & Houlihan 1988; Lyndon et al. 1992) and the incorporation of infused amino acids into proteins (Brown & Cameron 1991) are both associated with an increase in oxygen consumption (Brown & Cameron 1991; Lyndon et al. 1992). The extent of this stimulation in protein synthesis seems to be closely related to the size of the meal. Estimates made from results obtained from studies carried out on cod indicated that each gram of protein consumed resulted in a gram of protein being synthesised on the day of the meal (Houlihan et al. 1988). Subsequent measurements under-taken on Atlantic salmon and rainbow trout indicate that for every gram of protein consumed, 0.33–0.89·g of protein is synthesised (Houlihan et al. 1995a; Owen et al. 1999). It is to be ex-pected that the amount of protein synthesised will depend not only on the amount of absorbed protein but also on the amino acid balance of the protein and the digestible energy intake (see above). Only a proportion of the proteins that are synthesised following a meal are retained as growth. For example, in salmonids the retention effi ciency of synthesised proteins has been reported to fall within the range 23 to 62% (Houlihan et al. 1995a; Owen et al. 1999).

13.6 Long-term effects of food intake

Fish may be broadly classifi ed according to their feeding habits, e.g. plant eaters and detritus feeders, planktivores, benthophages and piscivores, and this is refl ected in feeding behav-iours, gut morphology and digestive physiology (Kapoor et al. 1975; Fänge & Grove 1979; Gerking 1994; Hidalgo et al. 1999). However, many species may display considerable intra-specifi c variation in trophic habits, with distinct phenotypes being associated with particular


patterns of prey or habitat use. Thus, certain individuals, or groups of individuals, may exploit only a small proportion of the array of prey types exploited by the species as a whole, and this trophic polymorphism is usually associated with a range of behavioural, morphological and physiological adaptations (Bryan & Larkin 1972; Meyer 1987, 1990a,b; Wainwright et al.1991; Mittelbach et al. 1992, 1999). Most of these adaptations seem to refl ect a phenotypic plasticity, rather than being genetic in nature, and they develop as a consequence of – rather than a prerequisite to – dietary specialisation. However, once developed, such dietary spe-cialisations may be self-perpetuating if increased specialisation on particular prey types leads to reduced capture effi ciencies for others (Bence 1986; Ehlinger 1990; Schluter 1995; Robin-son et al. 1996). These specialisations may involve changes in the morphology of the mouth-parts and gastrointestinal tract, and in digestive and absorptive capacities (Kapoor et al. 1975; Hofer 1979a,b; Buddington et al. 1987, 1997; Wainwright et al. 1991; Magnan & Stevens 1993; Mittelbach et al. 1999).

A phenotypic plasticity that enables individuals within a species to modify feeding behav-iours and regulate digestive functions in relation to changes in prey availability and dietary composition has obvious ecological implications; those species that are capable of making such modifi cations will be able to exploit a wider range of food resources. For example, there is considerable variation in jaw morphology and the size of the pharyngeal jaw mus-cles among populations of pumpkinseed sunfi sh (Lepomis gibbosus), much of this variation seeming to be associated with the proportions of snails making up the diet of the fi sh inhabit-ing different lakes or habitats (Wainwright et al. 1991; Mittelbach et al. 1992). Large differ-ences in jaw morphology and muscle size are inducible by providing pumpkinseeds with diets with or without snails, indicating that the differences among populations are predominantly the result of a developmental plasticity that allows the fi sh to exploit a range of prey types (Mittelbach et al. 1999). Fish may also have some capacity to adapt digestive processes, e.g. enzyme profi le and secretion, and nutrient transport and absorption, to match changes in diet (Kapoor et al. 1975; Hofer 1979a,b; Buddington et al. 1987, 1997), but this ability seems to vary among species. Carnivores, for example, appear to have a limited capacity to alter digestive and nutrient transport functions to match changes in dietary composition, whereas omnivores display a much greater ability to modulate their digestive and absorptive physiol-ogy (Buddington et al. 1987, 1997).

Diet-induced changes in gastrointestinal morphology are reasonably well documented in fi sh (Kapoor et al. 1975; Buddington et al. 1997), with high-roughage or nutrient-dilute diets tending to induce hypertrophy of the stomach and enlargement of the intestine. This enlargement of the GIT following feeding on foods of low nutrient density (Hilton et al. 1983; Ruohonen & Grove 1996) may represent one facet of the suite of adaptations that enable fi sh to maintain rates of nutrient, and energy, intake when provided with diluted feeds (Rozin & Mayer 1961; Grove et al. 1978; see also Chapter 11). Similarly, a common response to reduc-tions in feeding frequency or time-restricted feeding is an increase in meal size, presumably brought about by an increase in gastric capacity and hypertrophy of gut tissues. For example, plaice (Pleuronectes platessa) that were fed every other day developed larger and more bag-like stomachs than those fed more frequently, and the fi sh that were fed infrequently also increased their meal sizes to a greater extent than predicted (Jobling 1982). Hypertrophy of the GIT may commence shortly after the imposition of such feeding regimes, but some days or weeks may be required before the changes in the relative size of the GIT are complete, so


that meal size adaptations may occur gradually over time. This is what appears to occur when fi sh are exposed to time-restricted feeding regimes; feeding activity and/or feed intake of fi sh fed according to time-restricted regimes increases with the passage of time and gradually ap-proaches that of conspecifi cs allowed continuous access to food (Alanärä 1992; Boujard etal. 1996; Koskela et al. 1997).

The measurement of physiological effects over long periods allows identifi cation of changes that occur within an experimental population or in individuals. This provides a basis for the investigation of life history strategies, such as whether low or high protein turnover impact on long-term growth (e.g. Carter et al. 1998), or how feeding and growth link to the maturation of different individuals and strains (e.g. Sæther et al. 1996; Tveiten et al. 1996; Damsgård et al. 1999). Measurements can be made several times during the course of a study, and these can either be related to food intake directly preceding the measurements or to esti-mates of cumulative food intake. For example, fl ounder (Pleuronectes fl esus) were held for 212 days and nitrogen fl ux measured three times over this period; signifi cant relationships between protein intake and protein growth, protein synthesis and ammonia excretion were demonstrated (Carter et al. 1998). Studies of this type allow stable feeding regimes to be established, measurable growth occurs and repeated measurements of metabolic parameters can be made (Carter et al. 1993a,b; McCarthy et al. 1994; Owen et al. 1998). Results of such studies have, for example, supported the conclusion that individual differences in protein turnover have a marked effect on growth performance.

13.6.1 Protein intake, synthesis and growth

Tissue accretion (growth) is related to food intake, and when growth is defi ned as protein growth (Houlihan et al. 1995a,b) rates of protein growth will be determined by rates of protein synthesis and protein degradation. Measurements of protein metabolism can be made on in-dividual animals whose food consumption has been determined (see reviews by Houlihan etal. 1995a,b), and such investigations have revealed possible reasons for the wide differences between individual fi sh in the effi ciency of conversion of food into growth.

Protein growth is related to the amount of protein consumed through the stimulation in protein synthesis and effi ciency of retention of synthesised proteins, so analyses of rates of protein synthesis and protein growth should be combined with data on food intake (Houlihan et al. 1988, 1989; Carter et al. 1993a,b, 1998; McCarthy et al. 1994). Food intake appears to stimulate RNA synthesis, and this is indicated by an increase in the RNA:protein ratio. This probably provides part of the mechanism facilitating increased protein synthesis, so net growth occurs when rates of protein synthesis are higher than protein degradation (see Fig. 13.7). Protein growth is the difference between protein synthesis and degradation (see Fig. 13.7). A difference in protein growth between fi sh with the same food intake could be due to higher synthesis, lower degradation, or a combination of both. Individuals with high growth effi ciency have been compared to individuals with the same food intake but which grow more slowly. Improved effi ciency of conversion of food into growth seems to relate to lower rates of protein degradation (turnover) in the effi cient fi sh rather than to higher rates of protein synthesis (Carter et al. 1993b; McCarthy et al. 1994).

The infl uence of diet composition on protein synthesis and growth has also been investi-gated. Not only protein synthesis but also protein degradation (increased protein turnover)


can be correlated with increased protein intake (Houlihan et al. 1989; Meyer-Burgdorff & Rosenow 1995). Different methods, the short-term using fl ooding dose (Houlihan et al. 1989) and the medium-term end-product method (Meyer-Burgdorff & Rosenow 1995), have been used to measure protein synthesis. P. Campbell (unpublished data) found that as protein con-sumption increased (with no increase in ration or energy consumption), both protein synthe-sis and protein degradation increased in rainbow trout, and Meyer-Burgdorff and Rosenow (1995) reported that when common carp were fed high-protein feeds, both protein turnover and amino acid deamination increased. However, when the fi sh were fed low-protein feeds (sub-optimal protein concentrations), protein turnover was even higher, presumably due to increased recycling of amino acids (released from protein degradation) into protein synthe-sis. This result has also been found in rainbow trout fed diets with a poor amino acid bal-ance (Perera 1995), and supports the hypothesis that protein synthesis has a major role in the regulation of amino acid concentrations (see below, Amino acid fl ux model).

13.7 Amino acid fl ux model: food intake and amino acid fl ux

One aim of incorporating food intake data into an analysis of the physiological response to feeding is to construct fl ux diagrams. This is done in an attempt to analyse amino acid fl ux from the food into the free pools and hence into protein synthesis, protein growth and amino acid losses (Fig. 13.5). Such fl ux models are at an early stage of development, and represent an oversimplifi cation. Current models present a single free amino acid pool (ignoring differ-ences in free amino acid composition between tissues), and are based on estimates of whole body rates of protein synthesis. They also suffer from problems relating to differences in time scale between protein synthesis measurements and protein growth measurements (Houlihan et al. 1995b,c). Nevertheless, amino acid fl ux models are useful as they give an indication of the proportion of ingested protein which is retained as growth, and demonstrate the effects a meal has on the size of the tissue free amino acid pools and protein synthesis.

Intake

2.86 μmol AA

Protein Pool

6.36 μmol AA

Protein

Synthesis

4.44 μmol AA

Protein

Degradation

1.79 μmol AA

Protein

Growth

2.65 μmol

L

F

Fig. 13.5 Amino acid fl ux diagram for turbot larvae (at 17 days post hatch) fed with natural zooplankton, based on the model of Millward & Rivers (1988) and showing relative sizes for each component (redrawn from Conceicao et al. 1997). The values for the free AA (F = 0.24 μmol AA) and protein pools and for the rates of protein intake, synthesis, degradation and growth are from Conceicao et al. (1997). Values assume an average amino acid profi le where 1 g of protein was calculated to be equivalent to 8.1 mmol free amino acid. Amino acid losses (L) of 0.21 μmol AA were calculated as intake minus protein growth.


An amino acid fl ux model for turbot (Scophthalmus maximus) larvae has been constructed based upon intake values calculated from the amount of amino acids offered to the larvae each day (Conceicao et al. 1997). The model (Fig. 13.5) provides indications that a very high proportion (over 90%) of the ingested protein was retained as growth compared with values reported previously for larval herring (Clupea herengus) (60–65%) (Houlihan et al. 1995c) and juvenile fi sh (ca. 50%) (Houlihan et al. 1995a; Grisdale-Helland & Helland 1997). Pro-tein conversion effi ciencies for larval fi sh are not generally available because of the diffi culty of measuring food intake. Also, the estimates of amino acid intake are based upon the amino acid composition of the food offered. The fl ux diagram (Fig. 13.5) indicates that, on a daily basis, the dietary amino acid supply may be as much as ten times the free amino acid pool. Daily removal by protein synthesis was estimated to be twenty times the free amino acid pool, and protein breakdown was estimated to return ten times the free pool. Thus, the free amino acid pool of larval turbot is extremely dynamic, and it is possible that the amino acid profi le of the absorbed amino acids should match the requirements very closely if excessive amino acid oxidation is to be avoided.

An amino acid fl ux model constructed for larger fi sh (a 250-g rainbow trout consuming 2% body weight ration) revealed that consumption of amino acids was equivalent to approxi-mately twice the free amino acid pool (Houlihan et al. 1995c). Free amino acid pools in the majority of tissues are relatively stable following a meal (Carter et al. 1995a; see p.300, Tis-sue metabolic physiology), and they are regulated through anabolic and catabolic pathways. In the trout model it was estimated that protein synthesis removed 1.3 times the free pool; recycling of amino acids into the free pool through protein breakdown was equivalent to less than half its size, and losses of amino acid nitrogen above the maintenance rate were similar to the amount retained as growth (Houlihan et al. 1995c).

13.8 Biochemical correlates of food intake

It is to be expected that the greater amount of food eaten by fi sh, the greater will be the activi-ties and concentrations of enzymes involved in cellular metabolism (Houlihan et al. 1993). However, there are only a limited number of studies where such relationships have been in-vestigated at the level of the individual animal. More frequently the food intake of a group of fi sh has been measured and, because of the relationship between food intake and growth, the growth rate of individual animals has been correlated with the biochemical correlate under consideration. Thus, food intake of the group has been assumed to have driven both growth rate and the metabolic, or biochemical, correlate. Several metabolic variables have been used in an attempt to obtain some indirect assessment of the condition and recent growth history of fi sh (Bulow 1987; Busacker et al. 1990; Houlihan et al. 1993; Couture et al. 1998; Dutil etal. 1998). The metabolic indicators monitored include concentrations of nucleic acids, and enzymatic indicators of aerobic and glycolytic capacities of muscle, liver and intestine.

One frequently measured cellular component used as a growth correlate is RNA. RNA concentration is frequently expressed as a RNA:protein ratio on the grounds that this ratio correlates well with rates of protein synthesis, and the RNA:protein ratio has been described as the capacity for protein synthesis (mg RNA per gram protein; Sugden & Fuller 1991). Some 85% of total RNA is believed to be ribosomal, and it seems that the concentration of


the ribosomes has a major infl uence on rates of protein synthesis. Ornithine decarboxylase (ODC) is the fi rst and rate-limiting enzyme in the biosynthesis of nucleic acids and proteins (Benfey 1992; Benfey et al. 1994). Thus, it might be expected that changes in ODC activity would precede changes in other biochemical indices, e.g. protein synthesis, tissue amino acid incorporation and RNA:DNA ratios, used for the assessment of condition and short-term changes in fi sh growth. In brook trout (Salvelinus fontinalis) there was a positive correlation between hepatic ODC activity and gut contents (Benfey 1992).

The tissue RNA:DNA ratio has often been used as an indirect measure of recent growth in fi sh. It has been argued that because the DNA content of a cell is relatively constant, and RNA content varies with the rate of protein synthesis, the ratio of RNA to DNA provides an index of protein synthetic activity and hence growth (Bulow 1987); it is not, however, clear whether this argument is true for multinuclear muscle cells. In many studies with fi sh larvae it is the ratio of RNA to DNA that has been used as the growth correlate. For example, results of a recent study on cod larvae indicate that the analysis of nucleic acids may provide valu-able information about the recent growth and condition of individual larvae (McNamara etal. 1999). Concentrations of RNA, DNA, 18S ribosomal RNA (rRNA), poly(A) messenger RNA (mRNA) and two mRNAs coding for myofi brillar proteins were examined in cod lar-vae held in the laboratory under conditions of feeding and starvation. At the time of yolk exhaustion there were signifi cant differences between fed and starved larvae for all measured components. In an experiment with older larvae (3–4 weeks), 18S rRNA was signifi cantly reduced following three days of food deprivation, and mRNAs and total RNA responded in a similar manner (McNamara et al. 1999).

In a study carried out on juvenile cod where the animals were fed individually, the rate of food consumption was found to be positively correlated with white muscle RNA:protein ratio (Houlihan et al. 1989) and also to growth, protein synthesis and protein degradation rates (Houlihan et al. 1988). Data for Atlantic salmon gave similar relationships, and the strength of the relationships with food intake provided indications that the concentration of RNA (and by inference ribosomal numbers) was more important than ribosomal activity (i.e. grams of protein synthesised per gram RNA per day) (Carter et al. 1993b). Broadly similar results have been obtained with grass carp (Carter et al. 1993a) and rainbow trout (McCarthy et al.1994).

The strength of the positive relationships between RNA concentration and growth rate reported in many studies has led to various attempts to estimate the growth rates of wild animals from the RNA concentrations in their tissues (e.g. Mathers et al. 1992a,b; Pelletier etal. 1994). However, RNA concentrations in fi sh tissues may be affected by temperature and are also infl uenced by body size (Houlihan et al. 1993), and it is by no means clear that RNA concentrations always provide a good predictor of growth rate (Miglavs & Jobling 1989; Foster et al. 1993a; Pelletier et al. 1995). An additional complication is the time-course of the change in RNA concentration in response to the change in rate of food intake (Foster et al.1993b).

During periods of intense feeding the activity of white muscle enzymes, such as phospho-fructokinase (PFK) and 3-hydroxyacyl-CoA (HAD) appear to be positively correlated with feeding and growth rates (Kiessling et al. 1991a). The effect was not observed in the PFK activity of the red muscle. In small rainbow trout, as food intake increased, HAD and citrate synthase activities increased in red muscle but not in white muscle (Kiessling et al. 1991a).


Activities of mitochondrial enzymes, such as HAD, citrate synthase (citric acid cycle) and cytochrome oxidase (respiratory chain) in the white muscle may also be positively correlated with growth rates, but mitochondrial enzymes in red muscle appear to be poor predictors of growth. This is not surprising given the fact that during fasting it is the white muscle proteins that are mobilised, whereas the aerobic, red muscle seems to be preferentially conserved (Love 1988; see Chapter 15). However, there is not necessarily a strong link between enzyme activity, growth rate and food intake. No long-term effects were observed in white or red muscle enzyme activity of Chinook salmon (Oncorhynchus tshawytscha) despite a 20% in-crease in food intake when fi sh were exposed to increased water velocities (Kiessling et al.1994), indicating that food intake had no signifi cant effect on muscle metabolism per se. Both Walzem et al. (1991) and Bastrop et al. (1992) reported positive correlations between liver metabolism, growth and allotted ration level, so the liver seems to be an organ that is very responsive in terms of changes in enzyme levels in response to feeding (e.g. Bastrop et al.1992).

Enzyme systems that may be infl uenced by intensity of feeding are also to be found in the digestive system. For example, intestinal mitochondrial enzyme activity appears to correlate with feeding and growth (Couture et al. 1998; Dutil et al. 1998). Nutrient absorption by the enterocytes of the gut involves active transport (Buddington et al. 1987, 1997; Hirst 1993); this relates to Na+K+ ATPase activity, and the enterocytes are mitochondria-rich cells in which ATP is produced aerobically. Consequently, links between feeding intensity, intestinal mito-chondrial enzyme activity, nutrient absorptive capacity and growth might be expected. In the cod, chymotrypsin activity in the digestive caeca and alkaline phosphatase and glutamyl-transferase in the intestine have been found to correlate with the ingestion of food (Lemieux etal. 1999). The authors suggested that trypsin could be limiting growth rate in cod, and this has also been postulated for Atlantic salmon strains with different trypsin isozymes. The different trypsin isozymes may produce differences in free amino acid concentrations in the plasma (Torrissen et al. 1994; Rungruangsak-Torrissen et al. 1999).

13.9 Effects on body composition and growth effi ciency

Although the previous sections have emphasised the link between food intake and physi-ological responses, a more frequent approach is to relate food intake to whole animal growth. The relationship between food intake and wet weight growth has been described as being curvilinear. This means that above a certain level of food intake (defi ned as the optimum ra-tion) the rate of increase in growth declines and effi ciency decreases from its maximum value (Brett 1979; Elliot 1994; Jobling 1997). In many studies there has been a failure to differenti-ate between food provided and food consumed, leading to an overestimation of food intake and making interpretation of the data diffi cult (see Chapter 1 for discussion). In some studies in which food intake has been measured there is evidence for the curvilinear relationship (e.g. Jobling et al. 1989; Christiansen & Jobling 1990; Carter et al. 1992, 1994), and the same has been found in some studies in which cumulative food intake has been measured for fi sh held individually (e.g. Allen & Wootton 1982; Cui & Wootton 1988). On the other hand, a linear relationship between food intake and growth (Fig. 13.6) (e.g. Cui et al. 1994, 1996; Jobling 1995; Kiessling et al. 1995; Xie et al. 1997) or between protein intake and protein growth


(Fig. 13.7) is apparent in some instances. Thus, the form of the relationship between food consumption and growth is far from being resolved. There may be real species differences, confusion relating to the units used (absolute versus relative rates, wet versus dry weight, etc.) and temporal effects (see Jobling 1997 for discussion). The discrepancies may also refl ect

y = 0.93x - 0.16

R2 = 0.57

0

1

2

0 1 2

Food intake (% BW / d)

SG

R (

% / d

)

Fig. 13.6 The relationship between mean daily feed intake (% bw per day) and specifi c growth rate (% per day) of individually fed Atlantic salmon (700–1100 g) held at 9–14°C. (Adapted from Kiessling et al. 1995.)

Fig. 13.7 Summary fi gure of protein turnover (% per day) in fi sh as represented by relationships between: (a) protein intake (kc) and the capacity for protein synthesis (RNA:protein ratio); (b) protein intake and protein synthesis (ks) and protein degradation (kd); (c) protein synthesis and protein growth; and (d) protein consumption and protein growth (kg). Based on Atlantic cod. (Redrawn from Houlihan et al. 1988, 1989.)

3

4

5

6

7

8

9

0 1 2 3 4 5 6 7

kc (%/day)

RN

A:

pro

tein

0.0

0.5

1.0

1.5

2.0

0.0 1.0 2.0 3.0 4.0 5.0

ks (%/day)

kg

(%

/day)

0.0

1.0

2.0

3.0

4.0

5.0

0 1 2 3 4 5 6 7

kc (%/day)

ks

, k

d (

%/d

ay

)

ks

kd

0.0

0.5

1.0

1.5

2.0

0 1 2 3 4 5 6 7

kc (% / day)

kg

(%

/day)

(a)

(c)

(b)

(d)


problems encountered in measuring the relationship over the entire range of food intake, and under different environmental conditions.

In terrestrial mammals, where individual food intake measurements are easier to perform, fast-growing individuals have been shown to utilise feed more effi ciently than slow grow-ing animals (Tomas et al. 1991; Oddy 1999). In fi sh, this relationship has been far less well studied, partly due to the diffi culty in measuring food intake accurately (see Thodesen et al.1999). However, in most breeding programmes for fi sh it is assumed that the fastest-growing fi sh are also the most effi cient at utilising the feed (see Gjedrem 1983), and there is evidence that fi sh of fast-growing strains may have lower maintenance requirements than those of slower-growing strains (Kolok 1989).

There are perceived to be several benefi ts to be gained from the production of ‘single-sex’populations or sterile triploid fi sh for farming purposes (Donaldson & Devlin 1996; Maclean 1998). For example, sterile triploids are expected to grow better than diploids because of the allocation of resources to somatic weight gain rather than in the production of gonads. Further, the induction of sterility is envisaged to be a method that can be used to circumvent the problem of deterioration of fl esh quality that accompanies sexual maturation in several fi sh species. The expected differences between diploids and triploids have not always been observed, and the results of growth trials have been equivocal (Henken et al. 1987; Carter etal. 1994; Galbreath et al. 1994; Habicht et al. 1994; Galbreath & Thorgaard 1995; Ojolick et al. 1995; O’Keefe & Benfey 1999). Thus, in some cases triploids have been reported to outperform diploids, in others little difference has been observed, and in some studies the performance of triploid fi sh has been inferior to that of diploid conspecifi cs. In cases where food intake has been measured only minor differences between triploids and diploids have been recorded (Carter et al. 1994; O’Keefe & Benfey 1999), although there is some evidence that triploids may be competitively inferior when reared together with diploids.

Developments within the fi eld of molecular genetics are playing an increasing role in ag-ricultural production through the application of transgenic technology to enhance commer-cially important traits. Organisms into which new genetic material has been introduced are termed ‘genetically modifi ed’ or ‘transgenic’, and such organisms express proteins encoded by the introduced genes (Steele & Pursel 1990; Chen et al. 1995; Donaldson & Devlin 1996; Sin 1997; Maclean 1998; Prieto et al. 1999). Expression of peptide hormones, such as growth hormone (GH), in transgenic animals induces a series of physiological alterations relating to metabolism and growth, and it is transgenic fi sh for GH that have been the focus of most atten-tion (Chen et al. 1995; Donaldson & Devlin 1996; Maclean 1998; Cook et al. 2000a,b,c).

Fish transgenic for GH have accelerated growth and development relative to non-trans-genic conspecifi cs, results that are in line with fi ndings that application of exogenous GH also results in growth enhancement (Donaldson et al. 1979; Chen et al. 1995; Björnsson 1997; see also Chapter 12). Changes seen in fi sh transgenic for GH also seem to resemble those seen in fi sh treated with exogenous hormone (Björnsson 1997; Devlin et al. 1999; Cook et al.2000a). Thus, food intake of transgenic fi sh is greater than among non-transgenic conspecif-ics, and there are also differences in nutrient partitioning and body composition parameters, with transgenic fi sh tending to deposit less body lipid (Cook et al. 2000a). However, when large transgenic coho salmon were compared with their conspecifi cs (average body weight 4.5·kg), no differences in muscle structure were evident (A. Kiessling & R.H. Devlin, unpub-lished data), underlining the fact that the effects of very long-term exposure to elevated GH


levels are not well understood and may well be different from short-term exposure effects. Other changes seen in fi sh transgenic for GH are increased hyperplasia (Hill et al. 2000). Transgenic fi sh also display a suite of behavioural changes, including increased foraging activity (Abrahams & Sutterlin 1999) and increased competitiveness under conditions of restricted food supply (Devlin et al. 1999), that may enhance feed acquisition.

Metabolic rates of transgenic fi sh also tend to be higher than those of non-transgenic con-specifi cs (Stevens et al. 1998; Cook et al. 2000b,c). The increased metabolic rate may, in part, be a result of increased activity (Stevens et al. 1998; Abrahams & Sutterlin 1999) and increased feeding by the transgenics (Cook et al. 2000a), because an increase in food intake would result in a high metabolic rate due to HIF. This is, however, not the full explanation because transgenic fi sh maintain elevated metabolic rates even when food-deprived, and this results in a more rapid depletion of energy reserves than seen in non-transgenic conspecifi cs (Cook et al. 2000c). There are, for example, marked differences in rates of depletion in lipid reserves, possibly refl ecting the central role of GH in the catabolism of lipid during periods of food shortage. In other words, under conditions of food deprivation there appears to be an uncoupling of GH from the insulin-like growth factor system, and GH is directed away from growth promotion towards the regulation of lipolysis and catabolism (see Chapter 12). However, in GH transgenic coho salmon there were no differences in the β-oxidation enzyme HAD in the white muscle, but signifi cantly higher levels of the mitochondrial respiratory chain enzyme cytochrome oxidase and the glycolytic enzyme PFK – results that agree with the higher metabolic rates of these fi sh reported by others (Stevens et al. 1998; Cook et al.2000c).

Increased ration leads to increased growth (Brett 1979; Elliott 1994; Jobling 1997), with growth being a function of food intake in combination with the capacity for the fi sh to utilise the ingested food. The metabolism rates of ectotherms, such as fi sh, are low compared with those of endotherms of similar size, and are some fi ve to ten times lower even at the same body temperature. This means that maintenance requirements of fi sh are much lower than those of ectothermic vertebrates, and fi sh have considerable potential for the effi cient conversion of ingested food into somatic growth. Thus, when fi sh are held at temperatures close to the optimum, the maintenance ration is often found to be 15–25% of the maximum ration (e.g. Brett 1979; Cui et al. 1994, 1996; Elliott 1994; Jobling 1995; Mélard et al. 1996; Xie etal. 1997), and conversion effi ciencies in excess of 30% on an energy basis are frequently re-corded. However, the energetic costs of swimming are relatively high, and for fi sh consuming fi xed submaintenance rations there is an increased depletion of energy reserves at progres-sively higher swimming speeds. Similarly, the energetic costs of swimming may result in reduced growth in fi sh fed at fi xed rations that are above maintenance (White & Li 1985). On the other hand, increased swimming speed may lead to a stimulation of feed intake in fi sh allowed to feed to satiation, with the result that there is no negative effect upon growth rate but feed effi ciency is reduced (Fig. 13.8; Kiessling et al. 1994).

A variety of nutritional factors such as the amount and composition of the diet as well as the feeding regime can affect body composition, particularly body lipid (see Chapter 15). In long-term growth trials body size becomes a complicating factor (Shearer 1994). For example, it is well known that lipid deposition differed according to digestible energy intake, whereas body protein content (expressed as percent wet weight) was dependent on fi sh weight and


appeared not to be affected by food intake (Storebakken & Austreng 1987a,b; Kiessling et al.1991b; Shearer 1994).

The amount of food consumed is likely to affect a range of physiological systems in ad-dition to those already mentioned. The measurement of food intake of individuals in large groups allows the description of social hierarchies in terms of the proportion of the food consumed by each individual (see Chapter 3). For example, in Tilapia rendalli there was a correlation between feeding rank and dominance index when fi sh were fed from a point source (McCarthy et al. 1999). The effects of feeding and/or social hierarchy rank on brain serotonergic and dopaminergic activity (Winberg et al. 1993; Overli et al. 1998), fi n dam-age (Moutou et al. 1998) and stress (Christiansen et al. 1991) have also been examined. The emerging conclusion is that there are higher costs associated with being dominant or subor-dinate than being in the middle of a hierarchy (Moutou et al. 1998). Different facets of the abiotic and biotic environment can be manipulated to control the formation and strength of hierarchies, thereby restricting their physiological effects (see Chapter 6). For example, brain serotonergic activity was elevated in subordinate Arctic charr compared with domi-nants (Overli et al. 1998), but during subsequent rearing in isolation, food intake gradually increased in previously subordinate fi sh, while serotonergic activity fell to be close to that of dominants. The total amount of food available (McCarthy et al. 1992), as well as its spatial distribution and predictability of supply (Grand & Grant 1994; McCarthy et al. 1999), infl u-ence feeding, inter-individual variation in food intake and therefore physiological effects and growth.

Water speed can affect schooling behaviour in fi sh, and this may affect growth and growth effi ciency (see Chapter 6). Higher growth effi ciency of groups of Arctic charr subjected to sustained swimming was explained by lower energy expenditure associated with agonistic activity than for groups in static water (Christiansen & Jobling 1990). Differences between individual food intake (measured by X-radiography) and growth demonstrated that higher maintenance costs (and lower growth for a given food intake) were associated with static water (Christiansen & Jobling 1990). Interestingly, plasma cortisol concentrations were

0.5

0.54

0.58

0.62

0.66

0.7

Sp

ecific

gro

wth

ra

te (

%)

0.75

0.81

0.87

0.93

0.99

1.05

Fe

ed

eff

icie

ncy (

bo

dy w

eig

ht/

fee

d)

0.5 1 1.5 0.5 1 1.5

Body Length/sec

��

��

��

��

��

��

��

��

��

��

��

��

�� SGR

��FE

RL 100 RL 75

Fig. 13.8 Specifi c growth rate (% per day) and feed effi ciency ratio (g/g) in Chinook salmon exposed to different levels of sustained exercise (swimming speed, body lengths/second) and ration levels (RL100 and RL75). (Adapted from Kiessling et al. 1994.)


higher in fi sh forced to swim, and this was thought to refl ect general changes in metabolism rather than higher levels of stress (Christiansen et al. 1991). Some credence to this is given by the fi nding that the maintenance requirements of rainbow trout treated with cortisol im-plants (leading to chronic elevation of plasma cortisol concentrations) are higher than those of sham-treated and control individuals. In other words, elevated cortisol concentrations seem to result in ‘higher costs of living’ for the fi sh (Gregory & Wood 1999). Furthermore, chronic elevation of plasma cortisol concentration had negative effects on feed intake, growth and feed conversion in fi sh fed to satiation. Negative effects on growth and feed conversion were even more pronounced in fi sh provided with sub-maximum rations (Gregory & Wood 1999), which would be expected if treatment with cortisol resulted in increased metabolic costs to the fi sh.

One interesting area is the possible relationship between food intake and immunology. Lysozyme activity, which is thought to play a role in disease defence, was found to be reduced in rainbow trout fed a protein-defi cient diet (Kiron et al. 1995). Unfortunately this study, like many others, used dietary manipulations but did not control rates of food intake, beyond feeding to satiation. In another study, in which food intake of trout was determined, there were found to be signifi cant negative correlations between the amount of food consumed and lysozyme and antiprotease activity (Thompson 1993). This surprising result was also accompanied by a slight immunostimulatory effect of feed deprivation. The hypothesis that high feeding rates can result in immunosuppression, possibly as a consequence of pressure on metabolic scope, deserves to be further investigated.

13.10 Physiological effects and the regulation of food intake

Regulation of food intake is highly complex. It involves positive and negative feedback mechanisms acting over a hierarchy of time scales to determine the size of a single meal, the balance of essential nutrients and, in the long term, body composition (see reviews by Forbes 1988, 1992, 1999; Langhans & Scharrer 1992; Langhans 1999). Positive feedback determines the initiation and continuation of feeding, and results from relationships between the sensory properties of foods, experience concerning nutrient availability and the physi-ological status of the animal. Negative feedback can be divided into gastrointestinal and metabolic, or pre- and post-absorptive, phases (Langhans 1999). Forbes (1999) has argued that since the natural condition of an animal is to eat, only systems involved in the cessation of feeding need to be considered. Few reviews that concern the factors involved in regulating food intake in fi sh are available (see Peter 1979; Vahl 1979; Fletcher 1984; LeBail & Boeuf 1997; Silverstein et al. 1999), but the broad levels of organisation and integrated models proposed for mammals also appear to apply to fi sh (see Chapter 12).

We have attempted to integrate models of nutrient fl ux with models of food intake (Forbes 1999; Langhans 1999) in order to discuss physiological effects (Fig. 13.9). Thus, we adopt part of the ‘satiety cascade’ described by Blundell and Halford (1994), but omit reference to external information concerning the environment (e.g. temperature or photoperiod) and the food (e.g. appearance or smell). Three levels of regulation of food intake have been catego-rised, and these are designated short, medium and long term. Short-term regulation refers to factors that infl uence the size of a single meal (or daily intake), medium-term regulation


involves food intake over a period of days, and long-term regulation refers to regulation over periods of weeks to years (or complete life cycles). A factor is viewed as anything that elicits a response by the fi sh. Factors will include the physical bulk of food stimulating mechano-receptors in the stomach wall (short-term), nutrient imbalances that induce changes in food intake (e.g. stimulate intake of a feed with a high content of the limiting nutrient) with links to circulating levels of nutrients and metabolites (medium-term), and whole-body energy balance (long-term). Specifi c factors may be involved at more than one level, but the main purpose is to emphasise the importance of an integrated multifactorial approach to informa-tion transfer, rather than to consider specifi c neurological or hormonal pathways (see Chapter 12). The fi rst point of interest is in restricting the model to consider intake of a single feed of given composition. In the majority of experiments that investigate physiological effects a single feed is used, and a choice between two or more feeds is rarely given (e.g. Cuenca et al.1993). This means that varying the quantity consumed is the only mechanism available for controlling nutrient intake. This differs from the natural situation where fi sh can select prey that may differ in nutrient concentrations (Forbes 1999).

INTAKE

of a

SINGLE

DIET

[A] Short-term (Stomach emptying)

[B] Medium-term Increase in digestive

enzyme production.

Negative imbalance of one

essential nutrient.

[C] Long-term Low carcass fat / energy.

Increase in GIT capacity.

[A] Short-term Stomach filling.

High nutrient intake.

[B] Medium-term Positive imbalance of one

essential nutrient.

[C] Long-term Set-point carcass fat/

energy.

Stomach Intestine

GIT

CNS

Liver

Peripheral

Tissue

A

B

C

Body

Fat Feeding

Metabolism

Digestion

N

N

W

Information

Control

Nutrient flux

N. nutrient

R. recycling

W. waste

Body

Protein

B

N

B C

R

R

Blood

Fig. 13.9 Information fl ow involved in the physiological regulation of food intake via [A] short-, [B] medium- and [C] long-term factors acting from the GIT (gastrointestinal tract), blood, liver, peripheral tissues and the CNS. Nutrient fl ow (N) via food intake, nutrients absorbed from GIT and retained as growth; recycling of nutrients (R); waste following respiration or nitrogenous excretion (W).


In the gastrointestinal phase, several of the factors involved in short-term regulation relate to the capacity and fi lling of the stomach or intestinal-bulb in relation to its emptying and transfer of ingesta into the intestine. These factors may, in turn, be linked to feeding frequency and the physical and chemical properties of the food (Fänge & Grove 1979; Jobling 1987; dos Santos & Jobling 1991). In the medium term, feed composition may infl uence the produc-tion of digestive enzymes and the density of cell membrane nutrient transporters, resulting in changes in digestive and absorptive capacity (Kapoor et al. 1975; Buddington et al. 1987, 1997; Ferraris & Diamond 1989; Hirst 1993). Some of these factors may also act in the long term. For example, feeding fi sh with feeds of different bulk may result in the development of differences in the physical capacity of the GIT (Ruohonen & Grove 1996). The GIT is metabolically active (related to defence mechanisms as well as digestion and absorption), and has the potential to alter the composition of nutrients leaving it through both metabolism of dietary nutrients and via recycling (Reeds et al. 1999) (Fig. 13.9). It has also been suggested that blood-borne amino acids are metabolised preferentially by the GIT over dietary amino acids (Reeds et al. 1999). The consequences of this in the regulation of food intake relate principally to the short- and medium-term effects of circulating amino acids. However, little is known about the importance of these processes in fi sh, except that protein turnover in the GIT is high, as it is in the GIT of terrestrial animals (Houlihan et al. 1988).

When one feed is available, the relative importance of different factors in the metabolic phase is due to a balance between the negative (toxic) effects caused by the increased intake of some nutrients and the negative effects associated with low intake of others (Forbes 1999). These opposing forces will be mediated through circulating levels of metabolites or other physiological effects. For example, in mammals a high intake of dietary protein has negative effects associated with it (e.g. increased metabolism and body temperature; increased toxic nitrogenous waste in the blood), and under some circumstances food intake may be reduced to limit protein intake (Forbes 1999). Plasma concentrations of amino acids, glycerol and fatty acids and glucose have all been implicated in the regulation of food intake in mammals (Forbes 1992), but there is little information available concerning fi sh. Results of experi-ments run to determine protein and amino acid requirements indicate that food intake may be reduced when feeds contain either very low or high concentrations of the essential nutri-ent (see Chapter 11). This suggests that, like mammals and birds (Langhans 1999), fi sh are responsive to amino acids and avoid the metabolic consequences of an unbalanced amino acid intake. The poor ability of fi sh to regulate plasma glucose, as well as the low concentrations of glucose receptors in most tissues, argues against glucose being of major importance in the regulation of food intake under most circumstances (Peter 1979; Wilson 1994). However, it is probably more constructive to view the role of metabolites as part of a larger system in which their relative importance may change depending on a variety of endogenous and exogenous factors. Consequently, in the summary diagram, metabolites are depicted as being part of the fl ow of nutrients to the peripheral tissues via the blood and liver and also being subject to recycling (Fig. 13.9).

Responses based on circulating metabolites will act over the short to medium term. There are examples of experiments where feeds are used that contain extreme amounts of protein or specifi c amino acids (e.g. Rodehutscord et al. 1995), and fi sh seem to sense nutrient imbal-ance and regulate intake accordingly. Further, if fi sh are offered a choice of feeds they, like


other animals, appear to have the ability to adjust the intake of the different feeds in order to maintain a balanced nutrient intake (Cuenca et al. 1993; see Chapter 11).

HIF refl ects general metabolic activity following feeding, and it has been suggested that its magnitude may have an infl uence on food intake. As HIF increases, the scope for further metabolic activity decreases and the time-course of HIF should also refl ect an increase in metabolites in the blood (Vahl 1979). Since dogfi sh (Scyliorhinus canicula) consumed food (approximately 17% of a full meal) at the time of maximum HIF, HIF was viewed as not having the major infl uence on food intake in this species (Sims & Davies 1994). Similarly, Atlantic cod may consume additional meals under conditions where metabolic rates are still elevated due to the effects of HIF (Soofi ani & Hawkins 1982). Such experiments probably show the complexity of food intake control in that it is diffi cult to isolate the effect of a single factor when other factors are also exerting their effects.

That there is long-term regulation of body fat (or energy) to a set point (Kennedy 1953), thought to be primarily mediated via leptin and insulin, is generally accepted in mammals (Langhans 1999; see Chapter 12). Evidence for a similar long-term regulatory system in fi sh, although sparse, is becoming persuasive (Metcalfe & Thorpe 1992; Jobling & Miglavs 1993; Company et al. 1999; Silverstein et al. 1999). These studies show that attaining and maintain-ing a given energy status may be important for survival and reproduction. Both body protein and lipid should be considered as contributing to the ‘energy status’ (Fig. 13.9). Since fi sh species differ in their use of protein and lipid (and carbohydrate) reserves during feed depriva-tion (see Chapter 15), it will be of interest to see if these differences are refl ected in long-term regulation.

Food intake has an infl uence on many physiological processes, and it is important to be able to attribute cause to effect. Our attempt to model the regulation of food intake in fi sh highlights the need to consider an integrated approach rather than place too much importance on one or other factor. It is likely that the relative importance of different factors will change according to conditions such as the species, environmental characteristics or nutritional his-tory.

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Physiological Effects of Feeding

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