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1. Analysis of stable carbon isotopes is a valuable tool for studies of diet, habitat use and migration. However, significant variability in the degree of trophic fractionation (Δ13CC-D) between consumer (C) and diet (D) has highlighted our lack of understanding of the biochemical and physiological underpinnings of stable isotope ratios in tissues.
2. An opportunity now exists to increase the specificity of dietary studies by analyzing the δ13C values of amino acids (AAs). Common mummichogs (Fundulus heteroclitus, Linnaeus 1766) were reared on four isotopically distinct diets to examine individual AA Δ13CC-D variability in fish muscle.
3. Modest bulk tissue Δ13CC-D values reflected relatively large trophic fractionation for many non-essential AAs and little to no fractionation for all essential AAs.
4. Essential AA δ13C values were not significantly different between diet and consumer (Δ13CC-D = 0·0 ± 0·4‰), making them ideal tracers of carbon sources at the base of the food web. Stable isotope analysis of muscle essential AAs provides a promising tool for dietary reconstruction and identifying baseline δ13C values to track animal movement through isotopically distinct food webs.
5. Non-essential AA Δ13CC-D values showed evidence of both de novo biosynthesis and direct isotopic routing from dietary protein. We attributed patterns in Δ13CC-D to variability in protein content and AA composition of the diet as well as differential utilization of dietary constituents contributing to the bulk carbon pool. This variability illustrates the complicated nature of metabolism and suggests caution must be taken with the assumptions used to interpret bulk stable isotope data in dietary studies.
6. Our study is the first to investigate the expression of AA Δ13CC-D values for a marine vertebrate and should provide for significant refinements in studies of diet, habitat use and migration using stable isotopes.
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The carbon isotope composition at the base of the food web (δ13Cbase) ultimately determines the δ13C values of higher trophic level consumers. Without suitable estimates of δ13Cbase, which can vary both spatially and temporally (Vander Zanden & Rasmussen 1999; Graham et al. 2009), it is difficult to interpret consumer δ13C values using bulk SIA in light of potential changes in food web structure vs. variations in δ13Cbase (Post 2002). This can be particularly problematic when studying the diet and trophic dynamics of highly migratory marine organisms that move among isotopically distinct food webs (Estrada, Lutcavage & Thorrold 2005; Graham et al. 2009). There can also be significant variation in Δ13CC-D, ranging from −3 to +5‰, depending on consumer taxa, diet and tissues analysed (Gannes, O’Brien & Martínez del Rio 1997; Vander Zanden & Rasmussen 2001; McCutchan et al. 2003; Olive et al. 2003). Furthermore, the δ13C value of consumer tissue may not always follow bulk diet δ13C values because the carbon skeletons of different dietary constituents (proteins, lipids and carbohydrates) can be routed to different tissue constituents (‘isotopic routing’; Schwarcz 1991). Several studies have emphasized the problems that isotopic routing poses to the interpretation of stable isotope data in diet reconstructions (Parkington 1991; Schwarcz & Schoeninger 1991; Ambrose & Norr 1993). All of these factors can make interpretations of bulk tissue SIA challenging for studies of diet and migration, prompting a call for studies that examine the biochemical and physiological basis of stable isotope ratios in ecology (Gannes, O’Brien & Martínez del Rio 1997; Gannes, Martínez del Rio & Koch 1998; Karasov & Martínez del Rio 2007).
There have been very few controlled feeding experiments examining the trophic fractionation of individual AAs between diet and consumer (Hare et al. 1991; Howland et al. 2003; Jim et al. 2006). Studies to date found modest bulk tissue Δ13CC-D values (∼1‰) actually reflected an average of relatively large fractionations in many non-essential AAs and comparatively little fractionation in most essential AAs. However, there was considerable variation in Δ13CC-D across diets and individual AAs among studies. Furthermore, these studies all dealt with terrestrial vertebrates (pigs and rats), yet no controlled feeding experiments looking at compound-specific Δ13CC-D have been conducted on an aquatic vertebrate. Given the variability in bulk tissue Δ13CC-D across terrestrial and aquatic taxa (Vander Zanden & Rasmussen 2001; McCutchan et al. 2003), it is important to determine the mechanisms leading to variability in the fractionation of AA δ13C values for aquatic taxa.
We reared common mummichogs (Fundulus heteroclitus, Linnaeus 1766) on four isotopically distinct diets to examine trophic fractionation (Δ13CC-D) of individual AAs between diet and consumer. By choosing an herbivorous diet, two carnivorous diets and an omnivorous diet, we aimed to examine the potential variability in AA Δ13CC-D. We addressed the specific question: What is the isotopic relationship between diet and consumer for individual AAs in fish muscle? We focused on muscle tissue, because it is one of the most commonly used tissues in ecological studies of diet and trophic dynamics. We hypothesized that non-essential AA δ13C values would show evidence of both de novo biosynthesis and direct isotopic routing from dietary protein while essential AA δ13C values would only reflect isotopic routing. Similar results were found for pigs (Hare et al. 1991; Howland et al. 2003) and rats (Jim et al. 2006), although the magnitude and direction of trophic fractionation was quite variable. We also hypothesized that fish fed a high protein content diet would exhibit a greater degree of isotopic routing because routing is thought to be more efficient than de novo biosynthesis when non-essential AAs are sufficiently available (Ambrose & Norr 1993; Tieszen & Fagre 1993; Jim et al. 2006). Finally, we predicted that a deficit in non-essential AA abundance in diet relative to consumer tissue would result in higher trophic fractionation than would be expected from diets with excess non-essential AAs due to enhanced biosynthesis. Our study is the first to investigate the expression of individual AA Δ13CC-D values for an aquatic, vertebrate and should provide significant refinements to studies of diet, habitat use and migration using stable isotopes.
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Bulk δ13C values were significantly different among the diets (one-way anova, F = 717·7, P < 0·05; Fig. 1) and fish muscle (one-way anova, F = 321·8, P < 0·05; Fig. 1) across treatments. The Vegi-Pro diet had the highest carbohydrate content (73%) and lowest crude fat (6%) and protein (8%) content, while the squid and clam diets had the highest crude fat (18%) and protein (69% and 71% respectively) content and almost no carbohydrates (Table 1). Bio-Vita content was generally intermediate between the Vegi-Pro and the animal-based diets, with the exception of a high crude fat content (24%).
Figure 1. Mean (±SD) bulk tissue and individual amino acid δ13C values of (a) diet and (b) Fundulus heteroclitus muscle from four dietary treatments: Vegi-Pro (open squares), Bio-Vita (light gray triangles), squid (dark gray circles) and clam (black diamonds) (n = 5 replicates per treatment for diets and n = 3 tanks per treatment, consisting of three fish per tank for fish muscle).
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Table 1. Proximate analysis of moisture, crude protein, crude fat, crude fiber, ash and carbohydrate content (%) of four diets Vegi-Pro, Bio-Vita, squid and clam (n = 1)
The mean range in δ13C values across all 12 AAs analysed was 27·9 ± 6·9‰ for diet (Fig. 1a) and 23·6 ± 2·6‰ for fish muscle (Fig. 1b). We found significant differences in dietary δ13C values (Fig. 1a) among individual AAs (two-way anova, d.f. = 11, 96, F = 1239·0, P < 0·05) and among diet treatments (d.f. = 3, 96, F = 552·0, P < 0·05). However, variability in AA δ13C values was not consistent among diet treatments, generating a significant diet × AA interaction (d.f. = 33, 96, F = 21·71, P < 0·05). Fish muscle AA δ13C values (Fig. 1b) showed similar patterns to those of the diets, with significant differences among individual AAs (two-way anova, d.f. = 11, 96, F = 2681·0, P < 0·05) and among diet treatments (d.f. = 3, 96, F = 642·7, P < 0·05), including a significant interaction term (d.f. = 33, 96, F = 18·72, P < 0·05).
Despite significant variability in individual AA δ13C values in diet and muscle, there were several consistent patterns in our data. All AAs from the Vegi-Pro treatment, both diet and fish muscle, were the most 13C-depleted, while AAs from the squid and clam treatments were typically the most 13C-enriched. Glycine and serine were always the most 13C-enriched AAs in all treatments for both diet and fish muscle, where as valine, phenylalanine and leucine were always the most 13C-depleted AAs in all treatments. The δ13C value of aspartic acid, glutamic acid and proline were generally similar to one another in each treatment for both diet and muscle, although the values diverged more so for the Vegi-Pro diet. Finally, the non-essential AAs were 13C-enriched relative to the essential AAs by 7·5 ± 2·9‰ for diet and 7·3 ± 0·8‰ for fish muscle.
Muscle essential AA δ13C values showed stronger linear relationships to their respective dietary AA δ13C values with slopes closer to unity (m = 0·9 ± 0·2, b = −2·7 ± 3·8, r2 = 0·95 ± 0·04) than was found for non-essential AAs (m = 0·51 ± 0·14, b = −7·0 ± 3·5, r2 = 0·71 ± 0·21) (Table 2). Muscle essential AA δ13C values were also more closely related to their dietary AA δ13C values than they were to bulk diet δ13C values (m = 0·7 ± 0·4, b = −5·7 ± 11·7, r2 = 0·78 ± 0·18) (Table 2). Non-essential AAs δ13C values in muscle tissue typically showed stronger correlations to bulk diet δ13C values (m = 0·9 ± 0·5, b = 5·7 ± 15·3, r2 = 0·69 ± 0·26) than to their respective dietary AA δ13C values (Table 2).
Table 2. Slope (m), y-intercept (b) and R2 values from linear regression analysis of Fundulus heteroclitus muscle amino acid δ13C values compared to (a) dietary amino acid δ13C values and (b) bulk diet δ13C values
|Amino acid||(a) δ13Cmuscle-AA vs. δ13Cdiet-AA||(b) δ13Cmuscle-AA vs. δ13Cbulk-diet|
|Glycinea||0·40 ± 0·01||−3·09 ± 0·23||0·86 ± 0·07||1·43 ± 0·09||26·33 ± 1·74||0·86 ± 0·07|
|Serinea||0·62 ± 0·07||−2·92 ± 0·10||0·66 ± 0·01||1·73 ± 0·12||30·49 ± 2·26||0·89 ± 0·01|
|Argininea||0·67 ± 0·21||−5·09 ± 3·22||0·41 ± 0·10||0·53 ± 0·16||1·05 ± 6·07||0·39 ± 0·09|
|Aspartic acida||0·51 ± 0·11||−7·39 ± 1·67||0·77 ± 0·04||0·51 ± 0·12||−4·55 ± 2·54||0·55 ± 0·15|
|Glutamic acida||0·45 ± 0·11||−8·66 ± 2·16||0·93 ± 0·05||0·75 ± 0·24||−1·72 ± 5·05||0·84 ± 0·21|
|Prolinea||0·39 ± 0·10||−10·40 ± 1·81||0·46 ± 0·13||0·48 ± 0·13||−7·51 ± 2·80||0·35 ± 0·12|
|Alaninea||0·54 ± 0·06||−11·03 ± 0·97||0·92 ± 0·03||0·73 ± 0·08||−4·34 ± 2·04||0·93 ± 0·04|
|Threonineb||1·16 ± 0·10||1·82 ± 0·93||0·99 ± 0·01||1·15 ± 0·10||13·83 ± 1·94||0·83 ± 0·06|
|Isoleucineb||0·77 ± 0·24||−4·92 ± 4·37||0·91 ± 0·02||0·46 ± 0·13||−9·98 ± 2·54||0·87 ± 0·11|
|Valineb||0·87 ± 0·09||−2·84 ± 2·28||0·97 ± 0·05||1·10 ± 0·13||−1·14 ± 2·93||0·92 ± 0·11|
|Phenylalanineb||0·88 ± 0·16||−3·19 ± 3·95||0·96 ± 0·04||0·60 ± 0·11||−13·47 ± 2·31||0·80 ± 0·10|
|Leucineb||0·82 ± 0·17||−4·52 ± 4·35||0·95 ± 0·03||0·40 ± 0·10||−17·55 ± 1·99||0·47 ± 0·06|
|Mean NEAAa||0·51 ± 0·14||−6·95 ± 3·49||0·71 ± 0·21||0·88 ± 0·49||5·68 ± 15·28||0·69 ± 0·26|
|Mean EAAb||0·90 ± 0·20||−2·73 ± 3·84||0·95 ± 0·04||0·74 ± 0·35||−5·66 ± 11·71||0·78 ± 0·18|
Bulk fish muscle showed positive, albeit diet-specific, trophic fractionation (Fig. 2) for all treatments, with Vegi-Pro having the highest Δ13CC-D values and the squid and clam treatments having the lowest Δ13CC-D values. There was a large range in Δ13CC-D (12·5‰) values across individual AAs and dietary treatments (Fig. 2), from −7·9 ± 0·7‰ for glycine in the Bio-Vita treatment to 4·7 ± 0·5‰ for glutamic acid in the Vegi-Pro treatment. Even within individual AAs, the mean range in Δ13CC-D across all four diets was large (5·8 ± 2·9‰), ranging from aspartic acid (3·5‰) to glycine (11·2‰). While there was significant variability in Δ13CC-D values among diets and individual AAs, we observed several consistent patterns in the data. Essential AA Δ13CC-D values were very consistent among individual AAs (two-way anova, d.f. = 4, 40, F = 2·5, P > 0·05) and dietary treatments (d.f. = 3, 40, F = 1·7, P > 0·05). All essential AA Δ13CC-D values were not significantly different from 0‰ (mean Δ13CC-D = 0·02 ± 0·44‰) (one sample t-test, P > 0·05 for all essential AAs).
Figure 2. Bulk tissue and individual amino acid stable carbon isotope trophic fractionation (Δ13CC-D±SD) between diet and consumer for Fundulus heteroclitus fed four dietary treatments: Vegi-Pro (open squares), Bio-Vita (light gray triangles), squid (dark gray circles) and clam (black diamonds) (n = 3 tanks per treatment, consisting of three fish per tank).
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Conversely, Δ13CC-D values of non-essential AAs showed much larger deviations from 0‰ and considerably more variation among AAs (two-way anova, d.f. = 5, 48, F = 165·0, P < 0·05) and among treatments (d.f. = 3, 48, F = 218·4, P < 0·05), including a significant interaction term (d.f. = 15, 48, F = 35·1, P < 0·05). Only arginine in the Vegi-Pro treatment (one sample t-test, t = 0·8, P > 0·05) and glutamic acid in the Bio-Vita (one sample t-test, t = 0·3, P > 0·05), squid (t = 0·6, P > 0·05) and clam (t = 0·8, P > 0·05) treatments had Δ13CC-D values that were not significantly different from 0‰. Non-essential AA Δ13CC-D values generally followed the patterns observed in the bulk tissues Δ13C values (Fig. 2). Non-essential AA Δ13CC-D values were typically the most positive in the Vegi-Pro treatment with the exceptions of serine and arginine, where Bio-Vita showed the highest Δ13CC-D values. Conversely, Δ13CC-D values of non-essential AAs from the squid and clam treatments were never significantly different from one another (Tukey’s HSD post-hoc test, P > 0·05) and were generally the lowest values.
There was notable variation in the per cent abundance of AAs for both diets (Fig. 3a) and fish muscle (Fig. 3b). In general, the non-essential AAs glutamic acid, aspartic acid and arginine were the most abundant AAs. Although lysine was also quite abundant in both diet and muscle, it was not analysed for δ13C due to coelution with tyrosine. Leucine was the most abundant essential AA that was analysed for δ13C. The patterns of per cent abundance of AAs were very consistent across treatments for muscle (Fig. 2b), with a mean standard deviation of 0·1 ± 0·1% across all AAs. There was considerably more variation in AA per cent abundance across the four diets (Fig. 2a), with a mean standard deviation of 1·0 ± 0·8% across all AAs. In the Vegi-Pro and Bio-Vita treatments, all of the non-essential AAs analysed were less abundant in the diets than they were in the muscle (mean difference in per cent abundance, Vegi-Pro: −2·0 ± 1·6% and Bio-Vita: −1·5 ± 1·0%). The squid and clam diets usually, but not exclusively, had a surplus of non-essential AAs (0·0 ± 0·9% and 0·4 ± 1·2% respectively).
Figure 3. Mean per cent abundance (%±SD) of 16 individual amino acids (left axis) and the total per cent abundance of the 12 amino acids analysed for δ13C values (right axis) in (a) diet and (b) Fundulus heteroclitus muscle from four dietary treatments: Vegi-Pro (open bars), Bio-Vita (light gray bars), squid (dark gray bars) and clam (black bars) (n = 3 replicates per treatment).
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There was a significant negative correlation between the difference in non-essential AA per cent abundance in diet and muscle vs. AA Δ13CC-D (correlation coefficient, r = −0·43, P < 0·05; Fig. 4). Biosynthesized non-essential AAs tended to exhibit larger Δ13CC-D values when there was a greater deficit in AA per cent abundance in the diet relative to fish muscle. The Bio-Vita treatment showed the most variability in Δ13CC-D values, with the Δ13CC-D values of aspartic acid and proline in the Bio-Vita treatment closer those in the Vegi-Pro treatment and the Δ13CC-D value of glycine more similar to those in the natural animal diet treatments (Fig. 2). Both aspartic acid and proline showed large deficits in the Bio-Vita diet compared to fish muscle, as was the case for Vegi-Pro (Fig. 3). Conversely, glycine was much closer to the per cent abundance in muscle for the Bio-Vita, squid and clam treatments (Fig. 3).
Figure 4. Differences between amino acid per cent abundance in diet and muscle (mean %±SD) vs. stable carbon isotope trophic fractionation (Δ13CC-D±SD). Negative values signify a lower per cent abundance or δ13C value in the diet relative to the muscle respectively (n = 3 for per cent abundance and n = 3 tanks per treatment, consisting of three fish per tank for Δ13CC-D).
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We examined variability in carbon isotope fractionation of individual AAs in a common marine fish across a wide range of potential diets. Modest diet-specific Δ13CC-D values in bulk tissue reflected relatively large trophic fractionations for many non-essential AAs and little to no fractionation for all essential AAs. Essential AA δ13C values reflected a purely dietary signature with Δ13CC-D values near 0‰, making them ideal tracers of carbon sources at the base of the food web. Consumer non-essential AAs showed a large range in Δ13CC-D across diets and a variable, diet-specific degree of isotopic routing from dietary protein, which together may contribute significantly to the high variability in bulk tissue Δ13CC-D observed in the natural environment. The diet-specific fractionation we found should promote discussion about the assumptions of minimal and invariant bulk tissue carbon isotope fractionation in dietary reconstructions.
The patterns observed in the bulk δ13C values (Elsdon et al. 2010) were reflected in the δ13C values of individual AAs (Fig. 1). For instance, AAs from the Vegi-Pro treatment (diet and muscle) were always the most 13C-depleted, while those from the clam and squid treatments were typically the most 13C-enriched. This is not surprising given that protein was a significant component (up to 71%) of the diets (Table 1) and fish muscle, making AAs a major contributor to bulk tissue δ13C values. There were several consistent patterns in AA δ13C values across all treatments. The large range in AA δ13C values of diet (27·9 ± 6·9‰; Fig. 1a) and consumer muscle (23·6 ± 2·6‰; Fig. 1b) likely reflected the varied metabolic histories of these AAs. These ranges were similar to previous results on a variety of taxa including vertebrates (Hare et al. 1991; Fogel & Tuross 2003; Howland et al. 2003; Jim et al. 2006), invertebrates (Uhle et al. 1997; Fantle et al. 1999; O’Brien, Fogel & Boggs 2002) and plants (Fogel & Tuross 1999) from terrestrial and aquatic systems. This consistency likely reflects the influence of two main factors: (i) similarities in the major biosynthetic pathways that produce AAs in plants and animals and (ii) incorporation of dietary constituents directly into consumer tissue.
The patterns of Δ13CC-D of individual AAs generally mirrored those of the bulk tissue (Fig. 2), with Δ13CC-D values in the Vegi-Pro and Bio-Vita treatments significantly higher than those in the squid and clam treatments. A closer look at the Δ13CC-D values of individual AAs revealed some interesting insights into metabolic processes impacting the synthesis of muscle from dietary constituents. All essential AAs had Δ13CC-D values near 0‰ (Fig. 2), indicating no significant carbon isotope fractionation between diet and consumer muscle AAs. This observation was supported by the strong correlation and nearly 1 : 1 relationship between δ13Cdiet_essential_AA and δ13Cmuscle_essential_AA (Table 2). Small deviations from Δ13CC-D = 0‰, and thus a slope of 1, most likely represented minor kinetic isotope fractionation during catabolism or conversion of essential AAs to other metabolites. If we interpret the slope of this regression to be roughly equivalent to the proportion of carbon routed into muscle directly from the diet, the results support our hypothesis of a high degree of isotopic routing of essential AAs into consumer muscle. Our data support previous work on a variety of taxa and tissues (Hare et al. 1991; Fantle et al. 1999; Howland et al. 2003; O’Brien, Boggs & Fogel 2003; Jim et al. 2006), indicating that these findings are generally applicable to a wide range of taxa and tissue types.
Although plants and bacteria can synthesize essential AAs de novo, most animals have lost the necessary enzymatic pathways to synthesize these AAs at a rate sufficient for normal growth, and thus must incorporate them directly from their diet (Borman et al. 1946; Reeds 2000). As a result, the δ13C value of consumer essential AAs, such as phenylalanine and leucine, must represent the isotopic fingerprint of primary producers at the base of the food web (δ13CBase). It should be noted that this relationship could be obscured when dealing with strict herbivores that receive a significant contribution of bacterially synthesized AAs from their symbiotic gut microbial community (Rimmer & Wiebe 1987). The fidelity with which essential AAs reflect dietary sources makes compound-specific SIA a powerful tool for foraging ecology and dietary reconstruction. Essential AA δ13C values have provided insights into the diet of ancient humans and herbivores (Stott et al. 1999; Fogel & Tuross 2003), the allocation of adult resources to eggs in butterflies (O’Brien, Fogel & Boggs 2002; O’Brien, Boggs & Fogel 2003, 2005), the contributions of carbon sources to marine dissolved organic matter (McCarthy et al. 2004), and the importance of marsh-derived diets in supporting the growth of juvenile blue crabs (Fantle et al. 1999). This approach may also provide a powerful new tool for reconstructing the diet of highly mobile consumers that move among isotopically distinct food webs. Certainly compound-specific SIA avoids the confounding variable of determining whether consumers with different bulk tissue δ13C values represent feeding in the same food web but at different trophic levels, or feeding at the same trophic level but in isotopically distinct food webs (Post 2002).
Non-essential AAs showed significant deviations from Δ13CC-D = 0‰, and much greater variability both among AAs and across diet treatments compared to essential AAs (Fig. 2). This variability most likely reflects the influence of the varied metabolic processes that shape the isotopic signatures of non-essential AAs during biosynthesis. The Vegi-Pro treatment exhibited primarily positive Δ13CC-D values while the natural diet treatments, squid and clam, typically showed large negative Δ13CC-D values (Fig. 2). The large Δ13CC-D values that shifted muscle non-essential AA δ13C towards bulk diet δ13C values suggest a high degree of de novo biosynthesis. This hypothesis was supported by linear regressions between δ13Cdiet_non-essential_AA and δ13Cmuscle_non-essential_AA, where the mean slopes were far from unity (Table 2), indicating a disparity between the δ13C values of dietary and muscle non-essential AAs.
The high degree of biosynthesis is surprising for the three diets containing animal matter, Bio-Vita, squid and clam, given the high protein content of those diets (53%, 69% and 71% respectively; Table 1). Previous research suggested that when fed high protein diets, organisms typically route most AAs, including non-essentials, directly from diet as a means of energy conservation, because dietary routing is typically more efficient than de novo biosynthesis (Ambrose & Norr 1993; Tieszen & Fagre 1993; Jim et al. 2006). Fish, however, use a significant portion of dietary protein for energetic purposes (Kim, Kayes & Amundson 1991; Dosdat et al. 1996), and thus it is possible that fish exhibit a lower degree of dietary routing than terrestrial vertebrates. Only the Vegi-Pro diet had a low protein content (8%) that would likely require biosynthesis, resulting in the high Δ13CC-D observed across most individual AAs in that treatment (Fig. 2). Hare et al. (1991) found that δ13C of proline and glutamate differed by 5·7‰ in the bone collagen of pigs, suggesting that proline was being directly routed from diet into the consumer tissue. We found that proline had δ13C signatures closer to those of glutamic acid rather than dietary proline (Fig. 1b) and had Δ13CC-D values significantly different from 0‰ (Fig. 2). This suggests that proline was biosynthesized from glutamic acid via reduction through a Schiff base intermediate (Baich & Pierson 1965) rather than being directly routed from the diet.
Arginine in the Vegi-Pro treatment and glutamic acid in the Bio-Vita, squid and clam treatments showed strong evidence of isotopic routing directly from dietary protein (Fig. 2), yet evidence of biosynthesis in the other dietary treatments. Arginine is synthesized from glutamate via glutamyl-γ-semialdehyde and thus if arginine and glutamic acid were both biosynthesized or both isotopically routed, we would expect them to have similar δ13C values, as was the case for glutamic acid and proline discussed earlier. However, arginine and glutamic acid had different δ13C values, reflecting the different pathways leading to arginine and glutamic acid incorporation into fish muscle. Glutamic acid and arginine account for over 18% of the AAs in fish muscle alone (Fig. 3), and it is probable that other AAs can be directly routed as well. We found that when glutamic acid was biosynthesized in the Vegi-Pro treatment, it exhibited relatively large Δ13CC-D values (∼5‰) similar to the Δ13CC-D values Hare et al. (1991) and Howland et al. (2003) found for biosynthesized glutamic acid in pig bone collagen (∼6–7‰). Thus varying degrees of isotopic routing vs. de novo biosynthesis for these abundant AAs could significantly alter consumer tissue δ13C values relative to diet, further complicating the stable isotope relationship between diet and consumer.
We hypothesized that an underrepresentation of non-essential AAs in diet relative to muscle composition (Fig. 3) would necessitate a higher degree of biosynthesis than would be expected from diets with excess non-essential AAs. We found a significant correlation between diet and muscle AA per cent abundance and Δ13CC-D for biosynthesized non-essential AAs (Fig. 4). The AA composition of fish muscle is highly conserved (Wilson & Cowey 1985) as evidenced by the fact that muscle AA per cent abundance was very consistent across treatments (mean SD across treatments 0·1 ± 0·1%; Fig. 3b) despite feeding on diets with highly variable AA content (1·0 ± 0·8%; Fig. 3a). When there was a deficit in AA per cent abundance in the diet relative to the muscle, there tended to be greater trophic fractionation. This was particularly true for the Vegi-Pro and Bio-Vita treatments, where all non-essential AAs analysed were less abundant in the diets (Fig. 3a) than they were in fish muscle (Fig. 3b), and typically had the highest Δ13CC-D values. The disparity in AA per cent abundance was perhaps not surprising given that Vegi-Pro and Bio-Vita both contained plant matter, while the other diets were entirely animal protein.
Bio-Vita showed the most variability in Δ13CC-D values (Fig. 2), with some AAs trending towards Vegi-Pro and other towards the squid and clam treatments. For example, aspartic acid and proline had similar Δ13CC-D values in the Bio-Vita and Vegi-Pro treatments. Those AAs also showed large deficits in the Bio-Vita and Vegi-Pro diets compared to fish muscle. Conversely, glycine in the Bio-Vita treatment had a very negative Δ13CC-D value closer to those of the squid and clam treatments. In this case, the disparity in glycine per cent abundance between diet and fish muscle was small for the Bio-Vita, squid, and clam treatments. Differences in AA abundance in the diet relative to consumer muscle likely required varying the degree of biosynthesis and catabolism to meet the muscle composition demand, which may explain the corresponding shifts in AA trophic fractionation. However, disparities in diet and muscle AA composition alone only explain a relatively small fraction (r2 = 0·19) of Δ13CC-D values.
The differences in Δ13CC-D values between the Vegi-Pro treatment and the squid and clam treatments may reflect differences in utilization of the bulk carbon pool from a plant-based diet vs. an animal-based diet. The Vegi-Pro diet had far more carbohydrates (73%) than lipids (6%), while the animal-based diets showed the opposite trend (18% lipid, <1% carbohydrate (Table 1). The biosynthesis of non-essential AAs in the Vegi-Pro treatment appeared to rely on a more 13C-enriched carbon pool than the other treatments, possibly indicating a greater contribution of carbohydrates to the bulk carbon pool (Teece & Fogel 2007). Howland et al. (2003) reared pigs on a plant-based diet with a δ13C value close to the Vegi-Pro diet used in our study. Our results were similar to those of pig collagen Δ13CC-D values, showing large positive Δ13CC-D values for most non-essential AAs, particularly glutamic acid, proline and aspartic acid. Similar metabolic processes may, therefore, control Δ13CC-D values for many animals feeding on plant-based diets.
If lipids in the animal-based diets were being catabolized as a significant source of energy (Post et al. 2007), they would provide a very 13C-depleted carbon pool relative to bulk diet values (6–8‰; DeNiro & Epstein 1977) from which non-essential AAs were biosynthesized. This may explain why the Δ13CC-D values in the animal-based dietary treatments were significantly more negative than in the Vegi-Pro treatment (Fig. 2). The divergence in Δ13CC-D between Vegi-Pro and the squid and clam treatments is greatest for glycine, serine and alanine, which are also the first AAs synthesized from carbohydrates entering the glycolysis as glucose. Glucose is converted to 3-phosphogylcerate, which is the precursor for both glycine and serine. Alanine is synthesized from pyruvate several steps after 3-phosphogylcerate and showed less of a difference in Δ13CC-D between the plant- and animal-based diets. The remaining non-essential AAs are synthesized from oxaloacetate and α-ketogluterate intermediates many steps later in the TCA cycle and showed the smallest differences in Δ13CC-D between the plant- and animal-based diets. If different carbon pools are in fact driving the diet-specific differences in Δ13CC-D values of non-essential AAs, the impact appears to be greatest near the source of carbon entering glycolysis and gets diluted or altered as carbon flows through the TCA cycle. Our work supports previous observations that organisms feeding on apparently homogeneous diets can show substantially different δ13C values when routing of dietary components and alterations of available carbon pool δ13C values become important (O’Brien, Fogel & Boggs 2002; O’Brien, Boggs & Fogel 2003; Jim et al. 2006).
The diets chosen for this study ranged from solely plant matter to solely animal matter to examine the potential variability in diet to consumer carbon isotope fraction. Without knowing the fractionation between steps as lipid and carbohydrate carbon enter the TCA cycle and get incorporated into AAs, we cannot accurately predict how the precursor δ13C signatures will be manifested in the product AA δ13C values. The next step will be to identify the mechanisms behind the high, diet-specific variability in Δ13CC-D and determine what information non-essential AA δ13C values hold about consumer diet and metabolic history. This calls for targeted feeding experiments that track the fractionation of individual, potentially isotopically labelled dietary constituents as they are metabolically processed. While it is currently unclear how much useful information about diet and metabolic history is recorded in non-essential AA δ13C values, the fact that the Δ13CC-D values in both animal diet treatments tracked very closely and were always significantly different from the plant-based Vegi-Pro diet (Fig. 2) holds promise that there may be some valuable underlying principles controlling consumer individual AA δ13C values.