• Annelid;
  • δC-13;
  • δN-15;
  • fractionation;
  • isotopic enrichment;
  • lipid;
  • trophic


  1. Top of page
  2. Abstract
  3. Introduction
  4. Material and Methods
  5. Results
  6. Discussion
  7. Conclusions
  8. Acknowledgements
  9. References

Metazoan consumption of Bacteria and Archaea may impact key microbially mediated processes, yet techniques to quantify trophic linkages require laboratory evaluation before robust application to field observations are possible. In this laboratory-based study, an annelid belonging to a genus common at reducing habitats, Ophryotrocha labronica, was raised on eukaryotic, bacterial or archaeal food sources to test whether fatty acid and stable isotope paradigms are appropriate to quantitatively model metazoan consumption of microbial food sources. This annelid's δ13C tissue-diet shift, −3.6‰ to +3.6‰, was neither zero nor constant and was a function of the δ13C value and the C : N ratio of its food. Nitrogen isotope (mean δ15N) tissue-diet shifts ranged from −0.8‰ to −3.0‰ when raised in antibiotic-laden seawater in contrast to the tissue-diet shifts of +2.3 to +3.4 that are often used to define a species’ trophic level. The use of antibiotics to control microbial growth during the experiment appeared to have little effect on these fractionation values, except for individuals fed Spinacia oleracea that may have been impacted by the antibiotic treatment; when antibiotics were not used the δ15N value of O. labronica was not different from the S. oleracea that it consumed. Fatty acid profiles within this species were largely independent of diet. Polyunsaturated fatty acids, commonly used as a metric for phytoplankton consumption and not provided by the food sources, were present in O. labronica tissues regardless of food source. This suggests that O. labronica can synthesize these fatty acids. Whereas field studies have shown the importance of biomarker approaches, tissue-diet shifts based on the literature could erroneously characterize the diet and trophic level of this species. This is especially true in food webs that are known to rely on microbial production, such as those found at deep-sea chemosynthetic habitats.


  1. Top of page
  2. Abstract
  3. Introduction
  4. Material and Methods
  5. Results
  6. Discussion
  7. Conclusions
  8. Acknowledgements
  9. References

Understanding energy transfer throughout food webs, from bacteria to top predators, has been an underlying theme of ecology since shortly after the term ‘food chain’ was coined (Elton 1927; Lindeman 1942). The discovery that microbial processes, performed by both Archaea and Bacteria, provide diverse ecosystem services and facilitate biogeochemical cycling in pelagic (Partensky et al. 1999; Herndl et al. 2005) and benthic realms (Francis et al. 2005; Sommer et al. 2006) has led to renewed study of top-down forcing on bacterial communities (Pernthaler 2005; Frias-Lopez et al. 2009). Direct consumption of bacteria has been shown to decrease bacterial productivity (e.g. Lebaron et al. 2001; Spivak et al. 2007), increase bacterial productivity (e.g. Mikola & Setala 1998; Jiang 2007) and shift bacterial community composition (Duffy et al. 2003; Wardle et al. 2004; Spivak et al. 2007). As the role of grazing appears to be system- and species-dependent, quantitative techniques are necessary to allow rapid identification and differentiation of microbial food sources within a larger food web. Biomarker approaches, including stable isotope and fatty acid analyses, may provide a method to identify trophic linkages that are critical to ecosystem functioning through integrating microbial food sources into our understanding of food webs. However, laboratory-based experiments do not currently exist that allow interpretation of these analyses when dealing with bacterial and archaeal food sources. In this study I use a species of polychaete belonging to the family Dorvilleidae, a family that that is abundant within chemosynthetic habitats where food webs are based on bacterial and archaeal production (Thurber et al. 2012, 2013; Levin et al. 2013), to test the applicability of biomarker approaches for quantifying bactivory and archivory within metazoan food webs.

Stable isotope and fatty acid analysis are two techniques that can reveal food-web interactions. Generally, animals preferentially excrete 14N over 15N and respire 12C over 13C, leading to a changing isotopic ratio with each successive step within a food chain (Minagawa & Wada 1974; Peterson & Fry 1987; McCutchan et al. 2003). Isotopic ratios are reported as δ15N and δ13C notation as deviations from the isotopic ratios of atmospheric nitrogen and Vienna PeeDee Belemnite, respectively. In application, the carbon isotope shift between a species’ diet and its tissue, referred to as its tissue-diet shift or Δ13C, is small (between 0‰ and 1‰), making the δ13C of an organism a conservative record of the carbon source at the base of the food web rather than its trophic position (DeNiro & Epstien 1978). Δ15N, the tissue-diet shift for nitrogen, is not zero and rather constant among successive trophic levels, providing insight into the food source and trophic level at which a consumer feeds; δ15N often increases by 2.3–3.4‰ with each trophic level (Post 2002; McCutchan et al. 2003). Since this landmark observation of tissue-diet shifts (Minagawa & Wada 1974; Peterson & Fry 1987), the refinement and discussion of Δ13C and Δ15N has been the focus of many studies and reviews (Gannes et al. 1997; Vander Zanden & Rasmussen 2001; Post 2002; McCutchan et al. 2003; Boecklen et al. 2011). Accurate measure of Δ13C and Δ15N is key to using isotopic data to construct the quantitative models now employed to identify energy flow and trophic linkages (Phillips & Koch 2002; Schmidt et al. 2007; van Oevelen et al. 2010), yet few quantify fractionation factors associated with the consumption of Bacteria and Archaea.

Fatty acid analysis is based on the underlying assumption that many fatty acids (FAs) are incorporated from food items as it is energetically favorable compared to de novo synthesis. FAs are constituents of lipids including those that form cell membranes and vary by carbon length, double-bond position and branching pattern. Many food sources have either unique FAs or a unique distribution of FAs that can be traced into a consumer's tissue (Klein Breteler et al. 1999; Dalsgaard et al. 2003) although the approach lends itself to some environments better than others (Kelly & Scheibling 2011). While FA analysis has been applied qualitatively to trophic questions (Iverson et al. 2001; Kharlamenko et al. 2001; Thurber 2007; Drazen et al. 2008; Jeffreys et al. 2009), only a small number of studies of birds and mammals have measured the tissue-diet shift in both the abundance of specific fatty acids and the total fatty acid profile, ΔFA, necessary to gain quantitative information about a consumer's food source (Iverson et al. 2004, 2007; Iverson 2009; Wang et al. 2010). Furthermore, Archaea have lipid mono- or bilayers composed of repeating isoprene units ether-linked (rather than fatty acids ester-linked) to glycerol head groups, and therefore present additional challenges when using FA analysis to construct food webs (Thurber et al. 2012). The success of the these biomarker techniques directly rely on the accurate characterization of Δ13C, Δ15N and ΔFA, without which quantitative models are not possible.

A key group that has received little attention in tissue-diet shift laboratory studies is the ubiquitous annelids. This phylum is a dominant component of marine-sediment fauna throughout the world, occupying many trophic roles from grazers and deposit feeders to predators (Fauchald & Jumars 1979). The potential for trophic interactions between worms and the abundant microbes in the sediment make this group a likely consumer of Bacteria and Archaea. One family of Annelida, the Dorvilleidae, is well adapted to habitats with high microbial biomass. Dorvilleids are abundant members of reducing habitats (Levin et al. 2006, Levin et al. 2013; Bernardino et al. 2012; Thurber et al. 2012) and are known to feed on sulfide-oxidizing bacteria and methane-oxidizing Archaea (Levin & Michener 2002; Levin & Mendoza 2007; Thurber et al. 2012; Levin et al. 2013), making members of this family a model system to test measures of Δ13C, Δ15N and ΔFA. In this study, I used a laboratory-based approach to measure tissue-diet shifts between the dorvilleid Ophryotrocha labronica and food sources from each of the domains of life. This study tested the hypotheses that O. labronica's δ13C and lipid content reflects that of its diet and that there is a uniform increase in δ15N from O. labronica's food source to its tissue.

Material and Methods

  1. Top of page
  2. Abstract
  3. Introduction
  4. Material and Methods
  5. Results
  6. Discussion
  7. Conclusions
  8. Acknowledgements
  9. References

Ophryotrocha labronica, collected from an Italian harbor, has been in culture at the Scripps Institution of Oceanography (SIO) since early 2006. Adult stocks were raised on Spinacia oleracea until they deposited a brood that was then transferred to seawater without food; from this point on all seawater used (except where noted) was 0.2 μm filtered and contained two broad-spectrum antibiotics, 50 μm kanamycin monosulfate and 50 μm streptomycin sulfate, to eliminate or minimize microbial growth and processing of the food sources provided. While antibiotics are never 100% effective, may be potentially damaging to metazoans in high concentrations and can be degraded or assimilated, we chose to use this approach to minimize bacterial processing. Alternate approaches, including constant water changes, would have increased the stress upon O. labronica and antibiotics impact biofilm-forming bacteria in addition to water-borne bacteria. Upon hatching, single clutches were split among separate Petri dishes and fed one of the following freeze-dried foods: eukaryotic sources (i) S. oleracea (spinach), (ii) Oryza sp. (rice); bacterial food sources (iii) Photobacterium profundum 3TCK (a Gram-negative γ-proteobacterium), (iv) Bacillus subtilis (a Gram-positive firmicute); or archaeal food sources (v) Halobacterium salinarium, (vi) Haloferax volcanii (both halophilic Euryarchaea). All bacterial and archaeal food sources were provided by E. Eloe, SIO, from laboratory cultures. Spinacia oleracea and Oryza sp. were purchased locally. The same cultures and food stocks were used throughout the experiment, except for Halof. volcanii for which two cultures were grown from the same parent stock but the two cultures did not differ in isotopic composition. Food sources were provided in unlimited supply; approximately 1.6 mg of food was sufficient for up to seven individuals to grow from two to >10 setigers in a 22 °C incubator (or from 0.2 mm to a mean length of roughly 1.1 ± 0.4 mm and a maximum length of 2.3 mm). This took approximately 44−54 days and growth rate was not driven by food source (more information available in Thurber et al. 2012). When no food was provided there was 100% mortality of O. labronica. Individuals were harvested when they reached adult size (10−12 setigers) for both isotopic and FA analysis. Individuals were placed in filtered seawater overnight without food to allow gut evacuation (visible through their transparent body), rinsed in Milli-Q water, and frozen at −80 °C. A second experiment was conducted at Florida International University, in which this same stock of O. labronica was raised in the absence of antibiotics in filtered seawater. A single brood was separated into four replicate dishes, as the aforementioned experiment found no brood effect on isotopic signature, and raised to adult size on a diet of a different stock of S. oleracea to test the impact of antibiotics on estimates of tissue-diet shifts. The results of this experiment led to a more exploratory comparison between antibiotic and non-antibiotic laden seawater and a third experiment was conducted at Oregon State University, where four food sources (all aforementioned excluding Oryza sp. and Halof. volcanii) were provided to the same culture of O. labronica in seawater with and without antibiotics. In all cases the same microbial food sources were used; however, in each of the locations (universities) a different source of S. oleracea was used. In the final experiment at Oregon State a different supply of antibiotics was used.

Isotopic analysis was performed on two to four individuals per sample and a similar weight of each food (0.25 ± 0.02 mg). These samples were dried at 60 °C and acidified with either 10% platinum chloride in 1 N hydrochloric acid or 10% phosphoric acid (there was no significant impact of acid type on isotope signatures; paired t-test P > 0.05 for both C and N). Samples were analysed on either a Eurovector elemental analyzer interfaced with a continuous flow Micromass Isoprime isotope ratio mass spectrometer (irms) at Washington State University or a Thermo Finnigan Delta XP Plus with a Costech 4010 Elemental Analyzer at the SIO analytical facility. Precision of the instruments at the facilities was better than ±0.1‰ for carbon and ±0.3‰ for nitrogen. The realized precision at Washington State University was much better than this; the isotopic composition of the standard was measured as δ13C = −16.3 ± 0.03‰ and δ15N = 3.87 ± 0.00‰ (mean ± SD). In cases where comparable samples were run at both facilities there were no systematic discrepancies between the instruments.

Lipids were extracted using the method of Lewis et al. (2000) in a one-step extraction-transesterification reaction on freeze-dried material, a technique effective for small-biomass samples. All glassware used in the extractions was sonicated for 15 min with four washes (1 × soap, 2 × water, 1 × deionized water) and heated in a muffle furnace for 4 h at 500 °C. Contaminants were removed from the glassware by solvents following the same extraction protocol that the samples would undergo to remove any remaining lipids within the vials, and blanks were run concurrently with all sample sets. Worms or food sources were placed in these pre-extracted 12-ml screw-top glass vials with Polytetrafluoroethylene-lined lids at which point they were freeze dried. The extraction solvent, 3 ml of 10:1:1 methanol : chloroform : hydrochloric acid (v:v:v), was added, and the samples were ground with a glass rod in the extraction solvent and sonicated for 10−15 min. After heating to 90 °C for 1 h, samples were allowed to cool, and 1 ml of Milli-Q water was added. The newly formed fatty acid methyl esters (FAMEs) were extracted in three aliquots of 2 ml 4:1 chloroform : hexanes (v:v). Samples were blown to dryness in N2, massed and brought up in an appropriate amount of the chloroform : hexanes solution for injection and analysis by Gas chromatography-mass spectrometry (GC-MS) on a Thermo Finnigan Trace GC/MS with a TR-5MS 60 m × 0.32 μm i.d. column in positive-ion mode. Sample oven conditions were an initial hold at 60 °C for 1 min, heating from 60 °C to 180 °C at 12 °C per minute, then an increase to 250 °C at 2.5 °C per minute where samples were held for 30 min. Blanks were run with all batches and all solvents were ACS grade or better. All sample chromatograms were corrected for any peaks eluting in the blank. Owing to the small sample sizes, GC-MS analysis was chosen over gas chromatography-flame ionization detector to increase detection sensitivity, meaning that whereas internal comparisons within this study are valid, absolute concentrations are not quantitatively comparable with other instruments. FAs under 14 carbon lengths were not included in this analysis nor were peaks that were not FAs based on mass spectra. A 0.5% cut-off was used for inclusion in the analysis, eliminating FAs that were not greater than this value in any sample. Peak integration and identification were performed based on the mass spectra using XCALIBER software (Thermo Scientific) and comparisons to known standards (Supelco 37 Component FAME mix and Supelco Bacterial Acid Methyl Ester mix, Sigma-Aldrich), and dimethyl disulfide derivatization (following Nichols et al. 1986) for identification of mono-unsaturated bond location.

Statistical analysis was used to determine: (i) if there were differences among the δ13C and δ 15 N of food sources (one-way analysis of variance, ANOVA), (ii) if there were differences among isotope signatures of individuals fed those food sources (one-way ANOVA), (iii) if Δ13C or Δ15N were significantly different from zero (t-test between food source and consumer isotope composition). Regression analyses were performed between tissue and mean-diet isotope composition to identify linear relationships as would be expected from a uniform tissue-diet shift. Univariate statistical analysis was performed with SYSTAT v.10; San Jose, CA, USA and no transformations were necessary to fulfill the underlying assumptions of the tests. Homogeneity of variance was evaluated graphically and normality was tested using a Kolmogorov–Smirnov test. For ANOVA analyses, a Tukey post-hoc test was used to identify significantly different treatments. These statistical tests were performed on data from the initial antibiotic-laden seawater treatment, which had the most complete replication. A subset of the samples from the third experiment had anomalously low responses on the irms and failed quality control. These data were eliminated from the results, leading to insufficient replication for statistical analysis except for those individuals fed S. oleracea, for which the effect of antibiotics was tested using a one-way ANOVA as discussed above. For the FA profiles, multidimensional scaling (MDS) was used to plot differences in the overall lipid profiles within the tissue of O. labronica fed each of the food sources. A pairwise analysis of similarity (ANOSIM) tested whether food source was a determining factor in the lipid profile of O. labronica. Both MDS and ANOSIM were performed using log(x + 1) transformed data based on Bray−Curtis similarity in PRIMER (v. 6); Lutton, UK the transformation was used to improve the homogeneity of variance. In all instances, a significance level of 0.05 was used. Univariate statistical analysis was not performed on FA data because of abundant zeros, which made assumptions of homogeneity of variance invalid.


  1. Top of page
  2. Abstract
  3. Introduction
  4. Material and Methods
  5. Results
  6. Discussion
  7. Conclusions
  8. Acknowledgements
  9. References

Diet influence on carbon and nitrogen isotope signatures

Ophryotrocha labronica's diet influenced its isotopic composition but Δ13C was not uniform among food sources (Fig. 1). Food sources had distinct δ13C signatures from each other (F5,26 = 47.8; P < 0.001), with Photobacterium profundum being different from all other food sources and the remaining food sources each different from four of the other five (Fig. 1). Yet O. labronica did not retain a significantly different isotopic signature when fed these food sources (F5,19 = 2.338; P = 0.08) as would be expected if there was a consistent tissue-diet shift. Δ13C for all of the diets ranged from −3.6‰ to 3.6‰ but only the worms fed P. profundum and Oryza sp. exhibited significant isotopic differences between food source and tissue indicating a non-zero Δ13C (Table 1). Those that did have a significantly different Δ13C did not shift in the same direction; Oryza sp. caused an increase in consumer δ13C and P. profundum caused a decrease. The range of δ13C for individual O. labronica fed P. profundum was very large, ranging from −23‰ to −18‰, yet the consumer's δ13C was consistently lighter than its food source. There was no clear pattern of Δ13C as a function of the domain of the food source provided (Table 1). Both archaeal food source treatments yielded the smallest values of Δ13C and the eukaryotes and the bacteria had the largest Δ13C. Only the eukaryotic food sources had a significant Δ13C and they were opposite from each other. When looking across all treatments, there was a linear decrease in Δ13C as a function of δ13C of the diet as indicated by a slope not equal to 1 in a regression analysis where δ13Ctissue = −16.25 + 0.30 ×δ13Cdiet (R2 = 0.20, F1,23 = 5.87, P = 0.02; Fig. 2). The fit of this line was improved when food source C : N ratio was included as an independent variable resulting in δ13Ctissue = −13.59 + 0.44 × δ13Cdiet + 0.06 × C : N (Radj2 = 0.28, F2,22 = 5.58, P = 0.01). Oryza sp. had a high C : N ratio, which greatly influenced the fit of the line. This could be clearly seen when a regression was fitted both with and without Oryza sp.; By removing Oryza sp. from this regression analysis the R2 value increased from 0.20 to 0.34 (Fig. 2). Whereas these regressions do not explain much of the inherent variance of δ13Ctissue, indicated by the low R2 values, they do explain the mean values, suggesting that mean δ13Ctissue can be largely explained by mean δ13Cdiet when sample sizes are increased. When only means are considered across all treatments, 84% of the variance was explained by a regression, δ13Ctissue = −13.30 + 0.45 × δ13Cdiet + 0.07 × C : N (Radj2 = 0.84, F2,3 = 13.72, P = 0.03). This highlights that isotopic measures of a species based on one or two individuals are unlikely to characterize accurately the δ13C of the food source even when corrected for Δ13C.

Table 1. Mean tissue-diet shift for carbon, Δ13C, and nitrogen, Δ15N, and stable isotopic composition between Ophryotrocha labronica and six different diets. Statistics indicate differences in the stable isotopic composition between diet and tissue (df = degrees freedom and significant P-values are in bold). C : N ratio is given for each food source.
dietdomaintissue-diet shiftt-test between diet and Ophryotrocha labronicaC : N ratio ±SEper cent antibiotic Cbper cent antibiotic Nb
  1. a

    S. oleracea treatment where no antibiotics were added.

  2. b

    Potential amount of carbon or nitrogen derived from antibiotics used in the treatments estimated by a two-source mixing model where per cent antibiotic C or N = (δworm – δfood source)/(δantibiotic – δfood souce) based on Fry & Sherr (1984) assuming zero trophic fractionation for N and C.

Bacillus subtilis Bacteria0.2−1.0tdf = 7 = −0.19; P = 0.86; N = 8tdf = 7 = 1.7; P = 0.14; N = 84.1 ± 0.02118
Halobacterium salinarium Archaea−0.6−2.8tdf = 7 = 0.57; P = 0.59; N = 8tdf = 7 = 9.4; P < 0.01; N = 83.6 ± 0.04043
Haloferax volcanii Archaea−0.1−1.9tdf = 6 = 0.13; P = 0.91; N = 7tdf = 6 = 2.3; P = 0.06; N = 74.2 ± 0.23065
Photobacterium profundum Bacteria−3.6−0.8tdf = 8 = 3.4; P = 0.01; N = 9tdf = 8=1.3; P = 0.24; N = 93.8 ± 0.07017
Oryza sp.eukaryote3.6−1.4tdf = 10 = −4.8; P < 0.01; N = 11tdf = 10 = 1.3; P = 0.22; N = 1140.1 ± 2.862640
Spinacia oleracea eukaryote1.5−3.0tdf = 7 = −1.7; P = 0.14; N = 8tdf = 7 = 3.2; P = 0.01; N = 87.7 ± 0.961054
Spinacia oleracea a eukaryote−0.21.6tdf = 7 = −0.4; P = 0.70; N = 8tdf = 6 = 1.4; P = 0.21; N = 78.0 ± 0.480n/a

Figure 1. Carbon and nitrogen stable isotopic composition of six food sources and Ophryotrocha labronica fed those food sources. Significant differences in food sources are indicated by bars with horizontal bars showing significant differences in carbon and vertical differences in nitrogen. Points that fall under the same bar are not significantly different from each other. An asterisk indicates that the isotopic composition of that food source is significantly different from all other food sources. See text for statistical treatment. Error bars are SE.

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Figure 2. Relationship between (A): δ13Cdiet and δ13Ctissue and (B): δ15Ndiet and δ15Ntissue for Ophryotrocha labronica fed the indicated diets. Solid lines are linear regressions based on all data. Dotted grey lines indicate a slope of one, which is the slope predicted by a constant tissue-diet shift. Dashed black line indicates the regression when Oryza sp. was excluded from the analysis. See text for regression equations and fit. Error bars are SE.

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There was no consistent Δ15N for O. labronica, yet all food sources resulted in a decrease in δ15N (Figs 1 and 3). Nitrogen isotope values were not uniform among food sources or O. labronica fed those food sources. Halobacterium salinarium and Spinacia oleracea were less depleted in 15N than Oryza sp. and Haloferax volcanii (F5,26 = 7.52; P < 0.01; Fig. 1) and this resulted in a difference in O. labronica's δ15N for those individuals fed Halof. volcanii and Bacillus subtilis (F5,19 = 3.6; P = 0.02). Ophryotrocha labronica fed Halob. salinarium and S. oleracea were significantly different in δ15N from their food source with Δ15N values of −2.8 and −3.0, respectively. Oryza sp., the food that had the most distinct C : N ratio, had a Δ15N shift in its consumer's tissue similar to O. labronica fed a diet with a comparatively small C : N ratio. As with carbon there was not a slope of 1 between δ15Ntissue and δ15Ndiet, indicating that Δ15N varied with δ15Ndiet where δ15Ntissue = 0.23 × δ15Ndiet + 0.61 (R2 =0.29, F1,23 = 9.4, P < 0.01; Fig. 2). This relationship was not improved by including the C : N ratio of the food sources.


Figure 3. δ13C and δ15N of food sources and Ophryotrocha labronica fed those food sources with and without antibiotic treatments. Boxes indicate the isotopic ranges, horizontal lines indicate the value of each sample and crossed diamonds are mean with SE. Data that lack boxes had N < 3. If error bars are present without boxes, the error bars are the values. Without error bars, N = 1 and the crossed diamonds represent the measured value.

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The antibiotics were depleted in 15N compared with all the food sources, with kanamycin monosulfate (δ15N =−7.4 ± 0.4‰; mean ± SD, N = 4) and streptomycin sulfate (δ15N = −0.9 ± 0.5‰) together adding approximately 63 μg of nitrogen to each of the treatments. Together the antibiotics provided an N source that had a δ15N value of −2.3‰, based on a mass balance calculation. The carbon isotope signatures of the antibiotics were δ13C = −11.5 ± 0.3‰ and −12.5 ±0.1‰, respectively; combined they provided a potential C source that had a δ13C of −12.2‰. In certain treatments, water was replaced during the experiment, providing a sum total of 120 μg of nitrogen. 1.5 mg of each food source provided between 15 and 105 μg of nitrogen (relative input indicated by C : N in Table 1). A two-source mixing model was applied to identify the relative potential input of the antibiotics as a carbon and nitrogen source based on the δ13C and δ15N measured (Table 1). The estimates of the potential amount of antibiotics assimilated were different depending on whether carbon or nitrogen was used in the mixing model. There was no relationship between the amount of nitrogen provided by the food source and the amount of antibiotics estimated to be assimilated or the Δ15N value for that food source (regression between C : N ratio and Δ15N yielded a nonsignificant regression: R2 = 0.003, F1,4 = 0.01, P = 0.92).

When parallel experiments were run with and without antibiotics, the same overall shifts were observed with the exception of the individuals fed S. oleracea (Fig. 3). These experiments were run with a separate source of antibiotics whose C and N isotopic values were also different from the first batch. Kanamycin monosulfate (δ13C = −9.3 ± 0.15‰; δ15N = 2.0 ± 0.04‰; N = 3) and streptomycin sulfate (δ13C = −10.6 ± 0.34‰; δ15N = −3.57 ± 0.11‰; N = 3) together provided a potential source with δ13C = −10.2‰ and δ15N = −2.3‰ to the treatments, again based on a mass balance calculation. In all but S. oleracea, both treatments (with and without antibiotics) in all experimental trials fell within the range and spread of the points discussed above, further indicating that the antibiotic treatment did not impact these conclusions. A potential exception to this was O. labronica fed P. profundum without antibiotics, in which the δ13C values fell in the upper range of the same feeding trial with antibiotics, but skewed towards the heavier end. However, this is the opposite direction (in relation to its food source) from the δ13C provided by the antibiotics and thus unlikely to reflect assimilation of the antibiotics. The most perplexing results were from the feeding trials involving S. oleracea, in which case the antibiotic addition did impact the Δ15N. The mean δ15N of O. labronica fed this food source decreased from 5.0‰ to 1.9‰ when antibiotics were added. In this trial only the antibiotic treatment was different from the control and non-antibiotic treatment (F2,20 = 7.85; P < 0.01). Although I combined treatments from all three experiments (including three different sources of S. oleracea, raised individuals in water from both Atlantic and Pacific Oceans, and with two different antibiotic signatures) the apparent impact of the antibiotics when O. labronica is fed S. oleracea remains constant. While this may seem to dismiss the overall trend of a negative Δ15N, when O. labronica was fed Halob. salinarium, the other food source that resulted in a significantly negative tissue-diet shift, the Δ15N remained negative regardless of antibiotic addition (Fig. 3). As such, negative tissue diet shifts are possible for some food sources, regardless of the potential experimental artifact of antibiotic addition in this study. While the insufficient replication of this aspect of the study precludes robust statistical analysis, rendering these comparisons informative rather than conclusive, the observed negative Δ15N without antibiotics being present demonstrates that a negative Δ15N is not an artifact of my experimental design.

Diet influence on fatty acid signatures

The food sources provided a diversity of FAs, which differed in their chain length and branching pattern (Table 2). The most distinct food sources were the two archaeal species, which contained no FAs, and Bacillus subtilis, whose FA distribution was largely composed of branched FAs. Lipid extractions of both archaeal species were equivalent to concurrently run blanks. Oryza sp.'s profile had an abundance of an 18:2(n − 6), a FA also present in Spinacia oleracea; however this latter food source had 62% of its FA composition composed of a 18:3 FA. Photobacterium profundum contained the ‘classic’ Gram-negative bacteria profile, dominated by (n − 7) monounsaturated FAs. All eukaryotic and bacterial food sources contained the saturated 16:0 FA.

Table 2. Fatty acid (% FA±SE) composition of Ophryotrocha labronica reared on six food sources and the fatty acid composition of those food sources. Archaeal food sources had no FAs present.
fatty acid Ophryotrocha labronica Source
Bacillus subtilis (3)Photobacterium profundum (4)Oryza sp. (6)Spinacia oleracea (4)Halobacterium salinarium (7)Haloferax volcanii (3) Bacillus subtilis Photobacterium profundum Oryza sp. Spinacia oleracea
  1. a

    Indicates probable double bond position.

  2. Number of replicates is given in parentheses after the food source.

  3. tr, trace amounts.

  4. FAs are named after the number of carbons in their carbon backbone followed by the number of double bonds present.

  5. The (n − x) notation indicates the position of the first double bond (x) relative to the terminal end of the FA and those preceded by an i or a are branched.

14:03.2 ± 28.5 ± 3.16.1 ± 0.78 ± 1.58.2 ± 2.38 ±
15:011.7 ± 4.36.7 ± 4.02.8 ± 1.412 ± 5.811.6 ± 2.46.1 ± 2.426.0000
16:018.4 ± 5.126.3 ± 4.827.3 ± 2.231.7 ± 2.723.2 ± 4.027.8 ± 1.49.839.137.418.0
16:1 (n – 9)0.3 ± 0.30.1 ± 0.101.7 ± 0.80.6 ± 0.31.4 ± 0.70000
16:1 (n – 7)0.3 ± 0.32.7 ± 1.61.6 ± 0.90.9 ± 0.60.4 ± 0.20047.700
16:1 (n – 3)a0 0000 0 0001.8
16:20 0000 00005.6
17:06.6 ± 2.12.5 ± 1.51.8 ± 0.81.5 ± 15.3 ± 1.20.5 ± 0.50000
18:011 ± 423.0 ± 8.118.4 ± 2.821.5 ± 4.121.3 ± 5.435.3 ± 13.3001.8tr
18:1 (n – 9)3.5 ± 0.12.4 ± 0.88.6 ± 1.13 ± 1.32.2 ± 0.82.6 ± 1.90021.53.5
18:1 (n – 7)12.7 ± 0.514.2 ± 5.515.7 ± 1.97.8 ± 6.18.5 ± 3.36.2 ± 3.402.000
18:2 (n – 6)2.0 ± 0.41.2 ± 0.53.7 ± 0.60.5 ± 0.31 ± 0.41.3 ± 0.70038.09.1
18:30 0 0 0 0 0 00062.0
20:1 (n – 13)5.3 ± 0.71.0 ± 1.02.5 ± 1.41.8 ± 0.92.7 ± 1.33.1 ± 1.30000
20:20 01.4 ± 1.00000000
20:4 (n – 6)7.3 ± 3.42.5 ± 1.42.6 ± 0.90.5 ± 0.33.5 ± 1.72.6 ± 1.40000
20:5 (n – 3)2.0 ± 0.91.1 ± 0.70.9 ± 0.51.1 ± 0.71.2 ± 0.62.3 ± 1.40000
i15:07.5 ± 3.61.0 ± 0.40.9 ± 0.50.9 ± 0.30.5 ± 0.2035.8000
a15:01.2 ± 0.31.9 ± 0.90.5 ± 0.31.5 ± 0.91.3 ± 0.50.3 ± 0.30000
i16:02.1 ± 1.22.9 ± 1.90.4 ± 0.31.5 ± 1.53.6 ± 1.103.7000
i17:03.0 ± 1.60.1 ± 0.10.5 ± 0.40.1 ± 0.10.2 ± 0.1014.2000
a17:00.6 ± 0.40.5 ± 0.32.4 ± 1.82.4 ± 1.11.5 ± 0.42.4 ± 0.89.5000
i18:00.1 ± 0.100.2 ± 0.20.1 ± 0.11.3 ± 1.100000
cyclo180.8 ± 0.80.8 ± 0.50.3 ± 0.31.1 ± 1.10.4 ± 0.300000

Ophryotrocha labronica had a diverse distribution of FAs that were largely independent of those available from their food (Table 2). Individuals fed Haloferax volcanii had the least diversity, containing only 14 FAs, whereas the remaining food sources resulted in between 17 and 20 FAs in O. labronica's tissue. The FAs that were present in O. labronica's tissues included the two essential FAs, 20:4(n − 6) and 20:5(n − 3), as well as branched and one cyclic FA independent of what food source O. labronica was fed (Table 2); 20:4(n − 6) and 20:5(n − 3) were not provided by any of the food sources. There were significant differences in the FA profile of O. labronica when fed Oryza sp. and S. oleracea (R = 0.36, P = 0.04), and when it was fed B. subtilis and both Oryza sp. (R = 0.45, P = 0.01) and S. oleracea (R = 0.48, P = 0.03) based on the ANOSIM pairwise analysis, but there were no other significant pairwise comparisons. This was apparent visually as indicated by the absence of groupings defined by food source in an MDS plot (Fig. 4). No food source, regardless of how different its FA composition was from the other food sources, resulted in a predictable FA profile.


Figure 4. Multidimensional scaling of log(x + 1) fatty acid profiles of Ophryotrocha labronica fed six food sources. Worms fed eukaryotic food sources are in grey, bacterial in black and archaeal in white.

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Divergence from the mean FA distribution of O. labronica revealed subtle differences among the food-source treatments (Fig. 5; Table 2). Within the individuals fed B. subtilis there was a consistent enrichment of both i15:0 and 15:0 compared with worms fed other food sources. There was an increase of all three constituents of P. profundum in its consumer compared with the mean distribution of FA within O. labronica. Yet, P. profundum’s FAs were 39% 16:0 and this high concentration of this FA only resulted in a 0.5% increase in 16:0 in P. profundums consumer's tissue. In addition, P. profundum had 47% of its FAs made up of 16:1(n − 7) and this FA was <3% divergent among O. labronica fed any food source, even though P. profundum was the only species to provide this FA. Oryza sp. consumers had increased concentrations of four of the FAs provided by Oryza sp. but there was no resultant increase in 14:0. Individuals fed S. oleracea only appeared to incorporate 16:0 from their diet and had no assimilation of the 16:1(n − 3)*, 16:2 or 18:3 FAs (*indicates likely double bond position), which were either unique as in the first two cases, or completely dominant in the case of 18:3, constituting 62% of the S. oleracea's FA profile. Although there was large variance among replicates of O. labronica fed each food source, when this variance was removed (i.e. mean FA distribution in O. labronica as a function of food source was used), the signature of a given food source became apparent but the pattern of FA uptake among food sources was not uniform.


Figure 5. Deviation from the mean fatty acid profile for Ophryotrocha labronica fed six different diets. The mean fatty acid profile is the average per cent abundance of each fatty acid regardless of food source in O. labronica, and by subtracting it from the fatty acid profile of O. labronica fed each food source it highlights deviations in the fatty acid profile of O. labronica that result from the different food sources. Food-source fatty acid distribution is presented in the lower panel. FA, fatty acid.

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Although O. labronica appears to assimilate certain FA components from its diet, overall this species has a distinct FA signature that was independent of its diet. FA uptake was not uniform among food sources. By knowing the distribution of FAs within the food sources it was possible to find similarities between that source and O. labronica's FA profile, but without this a priori knowledge of the food sources it would not have been possible to discriminate any clear pattern (Fig. 4). Furthermore, O. labronica fed food sources that provided unique FAs, potentially useful biomarkers to identify consumers of that food source, did not always incorporate those unique biomarkers. This was highlighted by a lack of 18:3 in O. labronica fed S. oleracea. Ophryotrocha labronica appears to be able to synthesize every FA identified within its tissues, independent of its diet.


  1. Top of page
  2. Abstract
  3. Introduction
  4. Material and Methods
  5. Results
  6. Discussion
  7. Conclusions
  8. Acknowledgements
  9. References

General isotopic implications

The observed isotope tissue-diet shifts were both large in comparison with those previously found (McCutchan et al. 2003) and surprisingly these tissue-diet shifts were a function of the food source consumed. In this study, Ophryotrocha labronica fed all the domains of life had a Δ13C range of −3.6 to +3.6. This range is larger than the −2.7‰ to +3.4‰ found in a recent review covering many animal phyla (McCutchan et al. 2003). Previous investigators have found large ranges of Δ13C for polychaetes: −0.2 to 2.1 for Capitella capitata [sic] (Haines & Montegue 1979); +1.3 to +2.1 for Pseudopolydora kempi japonica (Hentchell 1998); and −2.2 to +3.9 for Hediste (Nereis) diversicolor (Jackson & Harkness 1987). Both C. capitata [sic] and He. diversicolor also had distinct shifts depending on their food source. Yet, these studies either lacked replication (Haines & Montegue 1979) or started with adults and relied upon tissue turnover during a 4-month period to evaluate Δ13C (Jackson & Harkness 1987). Data from the present study, which raised the model species from birth and took advantage of the increased throughput and decreased cost of isotopic analysis since 1979, support many of their findings. Yet, this phenomenon is not limited to annelids. Two recent studies found Δ13C values with a larger range than that observed in O. labronica, including a mammal whose Δ13C ranged from −8.8 to 0.6 (Caut et al. 2008) and an amphipod whose Δ13C ranged from −10 to −2 (Crawley et al. 2007), both of which were a function of the food source provided. In addition, similar findings that Δ13C is a function of a food source's δ13C have been found in a variety of cross-phyla studies (Hilderbrand et al. 1996; Felicciti et al. 2003; McCutchan et al. 2003; Caut et al. 2008, 2009).

Whereas a universal tissue-diet shift has been commonly applied to food-web studies, food quality and food amount in relation to metabolic needs impact the magnitude of Δ13C and Δ15N. Consumed food can be directly incorporated into a consumer's tissue or catabolized and respired/excreted or resynthesized prior to incorporation into its tissues (Auerswald et al. 2010). Within a food source, molecules are not homogeneous in their isotopic composition (DeNiro & Epstien 1977). This means that a consumer's tissue reflects the sum of many different tissue-diet shifts whose values are a function of differential incorporation and starting isotopic composition. Differential incorporation of food source molecules is manifested by proteins being largely directly incorporated into a consumer's tissue whereas carbohydrates and many lipids are catabolized before being rebuilt from components – as such proteins would have very low Δ13C and carbohydrates and lipids would have a larger Δ13C (Ambrose & Norr 1993; Fantle et al. 1999). This non-uniform reprocessing of compounds, called isotopic routing, can be especially important in mixed diets where one food source is higher in protein than the other food source. The high protein item will appear to be the dominant food source based on isotopic metrics even though it may be a minor component of the consumer's diet (Schwarcz 1991). Food sources with divergent C : N ratios cause greater tissue-diet shifts. A larger C : N ratio causes a greater Δ13C because of increased respiration and lower Δ15N as a result of nitrogen limitation (Webb et al. 1998; Adams & Sterner 2000; Phillips & Koch 2002). Greater amounts of food also allow rapid deposition of body mass, and consumer tissues will take less time to reflect the isotopic signature of the food source (Carleton & Martinez del Rio 2010). In addition, lipid synthesis causes a large isotopic fractionation for FAs (DeNiro & Epstien 1977), meaning that the more de novo FA synthesis performed by an organism the greater the depletion of 13C will be in that consumer's tissue. Neither archaeal food source provided any FAs to O. labronica, and both had negative Δ13C values as expected if de novo lipid synthesis was driving a portion of Δ13C (Table 1). However, these Δ13C were not significant, and the only significant and negative Δ13C value was from Photobacterium profundum, which appeared to provide at least some FAs assimilated by O. labronica, including 16:0, a FA that forms the basis for FA synthesis (Kattner & Hagen 1995). Therefore the balance between de novo lipid synthesis and assimilation did not appear to be a key factor in Δ13C. In times of famine, Δ15N is extremely high because the consumer's tissues are degraded during starvation and so 14N is excreted, creating an essentially infinite tissue-diet shift (Hobson et al. 1993). However, catabolic enzymes in marine organisms may not discriminate against 15N, leading to zero fractionation during starvation (Frazer et al. 1997; Mayor et al. 2011). In addition, Δ15N may be quite different for dissolved nitrogen sources. In any case, Δ15N values in this study were not indicative of starvation.

Acidification treatments can reduce the δ15N of a sample, which would appear as a reduced Δ15N (changing a predicted Δ15N from +2.4‰ to +1.1‰; McCutchan et al. 2003); however, this is not always the case and varies among groups analysed (e.g. Bosley & Wainright 1999; Carabel et al. 2006). In this study, the positive Δ15N for O. labronica fed Spinacia oleracea in the absence of antibiotics provides evidence that the acidification did not cause the negative or nonsignificant Δ15N that I observed for O. labronica fed most of the food sources. Many researchers use separate samples for δ13C and δ15N analyses to avoid this potential problem; however, in small organisms, especially those from deep-sea and chemosynthetic environments, where only a few individuals are available for analysis and single individuals may not provide sufficient biomass for separate analysis, coupled analysis is still necessary and common.

In this study I attempted to minimize many of the aforementioned artifacts associated with tissue-diet fractionation and yet still observed a food source-dependent tissue-diet shift. By raising O. labronica from hatching on a prescribed diet I avoided problems with incomplete isotopic turnover from previous food sources. Isotopic routing impacts on these estimates were minimized as all food sources were fed in monoculture and the whole organism was sampled, eliminating divergent assimilation among tissue types analysed. The C : N ratio did impact Δ13C but to a lesser extent than the starting food source δ13C.

The negative Δ15N values present in the S. oleracea treatment that included antibiotics potentially identified a methodological bias within this experiment. A variety of plausible explanations may explain this feature. Invertebrates have been shown to use dissolved organic food sources to augment particulate food (Rau & Anderson 1981; Manahan 1990). In this study, the antibiotics provided a potential organic nitrogen source that was on the same order of magnitude in concentration as the nitrogen provided by the food sources and the antibiotic's δ15N could explain the negative Δ15N (Fig. 1). If the antibiotics were consumed it would be expected that the carbon from the antibiotics would also be consumed and the food sources that provided the least nitrogen would have the greatest assimilation of antibiotic nitrogen. Neither of these phenomena occurred, although differential incorporation of nitrogen and carbon can result, especially if there are discrepancies among the nutritional values of the food sources (Podlesak & McWilliams 2006). Δ15N for Oryza sp. was not significant and was less than Δ15N for Halobacterium salinarium and S. oleracea even those these latter two provided five times the nitrogen of Oryza sp. (Table 1). An alternate mechanism by which the antibiotics may have impacted Δ15N is through altering any gut symbiont−host relationships. This is potentially the most likely explanation for O. labronica fed S. oleracea, as this appeared to be the only feeding assay that was influenced by the antibiotics. Heterotrophic annelids have been known to have a variety of bacterial symbionts, including denitrifying bacteria (Karsten & Drake 1997), a group that can cause δ15N changes much greater than 10‰ (Mariotti et al. 1981). Additionally, it cannot be ruled out that the nitrogen was taken up through absorption rather than dietary assimilation (Montagna & Bauer 1988).

It is not conclusive that the negative Δ15N values were caused by the antibiotics as (i) negative, often unexplainable δ15N values are found in a variety of field studies, (ii) the range of values observed within the individuals fed in the absence of antibiotics encompassed that of the food source and (iii) the negative Δ15N of individuals fed Halob. salinarium was not impacted by the presence of antibiotics. δ15N values reduced below 0‰ have been seen in a variety of heterotrophic fauna from deep-sea methane seep settings (e.g. Levin & Michener 2002; Levin & Mendoza 2007; Thurber et al. 2010), hydrothermal vents (Colaço et al. 2002), and lab-based studies (McCutchan et al. 2003). In addition, if the deviation from literature values of Δ15N was caused by the presence of antibiotics, when the antibiotics were not added there should have been a significant difference between food source and tissue and a Δ15N >2.3‰, neither of which occurred, even for individuals fed S. oleracea. While it is possible that the antibiotics may have augmented O. labronica's diet, they were not the main source of food. The gut of O. labronica was obviously full of the food source it was provided, and anecdotally, when this species was not fed sufficiently it did not survive on antibiotics alone at the concentration provided. In the instance where the same source of S. oleracea was fed to O. labronica with and without antibiotics, the range did overlap and thus there may be a potential influence on the nutritional source of S. oleracea used. Further study is clearly necessary to identify the role of antibiotics, host–gut symbiont interactions, dissolved organic nitrogen and food source in measured values of Δ15N. Regardless, this study shows that negative Δ15N occur and that food-web studies that apply a uniform and positive Δ15N may misidentify the trophic level of a consumer.

Essential fatty acids in annelids

A surprise from this laboratory study was the ubiquity of the essential FAs in individuals that were fed diets that did not contain essential FAs, suggesting the presence of desaturases not known to occur within most animal phyla. Essential FAs are those that cannot be synthesized using desaturases, the enzymes that add double bonds to FAs, known to occur in most Metazoa (Berge & Barnathan 2005); however, this paradigm is rapidly changing with further directed study (Monroig et al. 2013). Ophryotrocha labronica appears to be able to synthesize the polyunsaturated fatty acids (PUFAs), 20:4(n − 6) and 20:5(n − 3) from diets that do not include any FAs, i.e. the two archaeal food sources, and diets that do not provide the precursors for their synthesis, the two bacterial food sources. Although Spinacia oleracea provided both 18:3 and 18:2 FAs, the precursors that are used in terrestrial systems to form PUFAs, O. labronica fed S. oleracea had lower PUFAs than those fed other diets. There is some debate as to whether or not these starting points are functional for marine systems and thus may not act as precursors for this species (Pond et al. 2002). Without showing the specific enzymatic pathway or the presence of those necessary desaturases, this study can only suggest that O. labronica is able to synthesize essential fatty acids. In addition to this study, the most compelling evidence that supports the ability of Polychaeta to synthesize PUFAs comes from reducing habitats: 20:5(n − 3) and 20:4(n − 6) are both found in the symbiont-bearing, mouthless and gutless hydrothermal vent worm Ridgea piscesae (Pond et al. 2002), a methane seep frenulate (Lösekann et al. 2008) and a methane seep archivorous dorvilleid (Thurber et al. 2012). The latter example was found within authigenic carbonates and had 20:5(n − 3) and 20:4(n − 6) FAs with δ13C isotopic signatures of −103‰ and −109‰, respectively, clearly indicating nonphotosynthetic origin and likely synthesis; these PUFAs were not found in the habitat that the worms were collected from. More evidence of de novo synthesis by an annelid comes from a heterotrophic, hydrothermal vent species, Paralvinella palmiformis, that subsists on bacteria but has PUFA concentrations similar to shallow water species (Taghon 1988). Nematodes (Spychalla et al. 1997), harpactacoid but not calanoid copepods, mollusks (Monroig et al. 2013), heterotrophic ciliates and flagellates (Klein Breteler et al. 1999; Zhukova & Kharlamenko 1999) are now known to be able to synthesize these FAs and further research is warranted to determine if annelids may as well.

Fatty acid analyses in food webs

While effort was made to minimize microbial reprocessing of the food sources throughout this experiment, it is unlikely that all microbial growth was completely eliminated. Microbial fungal growth and input to the feeding trials is a possibility; however, if fungus were a dominant food source a uniform isotopic signature among individuals fed each of the food sources should have been present, which was not the case (Fig. 3). In addition, it is unlikely that fungi would have impacted the results similarly at three different laboratories and when both Pacific and Atlantic source water was used. 15:0, 17:0 and branched FAs were present in Ophryotrocha labronica fed all of the food sources. These FAs are thought be derived exclusively from microbial biomass. The least affected of all was O. labronica fed the Archaea, Haloferax volcanii, and this food source still resulted in 9.6% of the total FAs within O. labronica appearing to be bacterial (15:0, 17:0 and branched FAs). Unlike the aforementioned siboglinid polychaete, Ridgea piscesae, the dorvilleids are not known to have chemoautotrophic symbionts. Annelids however, are known to have microbial flora that aid in digestion and could impact biomarker uptake and modification, including essential FA formation (Sampedro et al. 2006). As O. labronica was able to grow to reproduction on all food sources, with no change in growth rate (Thurber et al. 2012), in no instance did the antibiotics used eliminate necessary processing of the food sources by potential gut symbionts. However, increased gut flora processing would have further differentiated the FA profile of O. labronica from that of its food sources. Microbial processing may be an integral part of how a food source is reflected in the tissue of a consumer and an inherent aspect of using biomarkers to identify a species diet.

Fatty acid analysis has been shown to be a powerful tool to identify qualitative food web links and can provide quantitative application in certain systems, yet as shown here, great care must be used when interpreting field results without careful laboratory study. In a landmark paper, Iverson et al. (2004) was able to use laboratory-based analysis of a marine mammal to derive a model sufficient to provide reliable tissue-diet shifts for each of the FAs present within the consumer's tissue. They were then able to accurately apply this in the field. Within the Annelida, Capitella sp. has been shown to have a FA composition reflecting its diet (Marsh et al. 1990), yet the diets tested in that study provided 18 different FAs in contrast to this study in which each of the food sources provided between zero and seven FAs. This resulted in O. labronica having to synthesize most of its FAs and likely led to FA profiles distinct from those of this species’ diet (Fig. 5). In a study similar to this one, ciliates and flagellates were fed food sources that lack FA diversity, and this resulted in a similarly large diversity of FAs in these consumers’ tissues (Zhukova & Kharlamenko 1999). This finding suggests that when a food source is limited in FA diversity, the FA signature of the consumer reflects its diet less. In addition, many short chain (i.e. 16:0 and shorter) FAs are catabolized rather than incorporated, contributing to why O. labronica does not reflect its diet – 16:0 was the dominant FA of three of the food sources present, with other short chain FAs being present along with them. As bacteria commonly have a profile dominated by short chain FAs, it is likely that bacterial FAs are routinely under-represented in bactivorous fauna. As no unique archaeal biomarkers were found within the FAs of the consumer, even when analyses aimed at targeting archaeal biomarkers were used, Archaea are not resolvable within a FA-derived food web. Instead, archaeal lipids are digested and the C from them likely used to synthesize FAs (Thurber et al. 2012).

For complex invertebrate food webs, FA analysis has been applied successfully to determine divergent food sources, and is therefore a valid approach for identifying interactions (e.g. Kharlamenko et al. 2001; Colaco et al. 2007; Drazen et al. 2008; Thurber et al. 2013). Yet as shown here, not all biomarkers are reflected in a species’ diet. When temperature, metabolism and species were held constant, only Bacillus subtilis resulted in enrichment of O. labronica's tissues in diet-provided FAs, and even then O. labronica's lipid pattern was discernible from only two of the other food sources. The absence of unique dietary FAs in the tissue of a consumer does not suggest that it avoids a particular food source. These results show that cellular machinery can be more important than diet in the FA profile of certain invertebrates. This may be because, unlike ‘higher’ organisms, annelids are adapted to FA-poor diets and thus have a greater abundance of desaturases, or gut symbionts, than is currently recognized. It remains to be shown if this species’ FA signature will more closely represent its diet if it is fed a high quality food source.

Food web implications for deep and chemosynthetic habitats

Fatty acid and stable isotopic approaches have been routinely employed since shortly after vents and seeps were discovered (e.g. Childress et al. 1986; Fiala-Médioni et al. 1986; Taghon 1988), largely because of the remoteness of these habitats and the inherent challenges that confront those who study them. Deep-sea vent and seep production is largely performed by Bacteria and Archaea (Fisher 1990; Levin 2005), and, just like the surrounding deep-sea fauna, whose food is stripped of essential FAs as the food sinks through the water column (Wakeham et al. 1997) provide limited access to those FAs thought to be needed for growth and reproduction. Many, but not all Bacteria (Nichols 2003) do not form essential FAs and therefore deep-sea animals that normally subsist on Bacteria either require periodic photosynthetic deposition, such as seasonal phytodetritus pulses (Billett et al. 1983), or the ability to synthesize FAs de novo to gain PUFAs. Through the results of the present study, in addition to the enigmatic presence of PUFAs in many annelids that do not appear to rely on photosynthetic production, it is clear that any conclusions based on the presence of these compounds alone could be incorrect as to the relative role of photosynthetic input into deep-sea habitats. Thurber et al. (2013) found PUFAs in fauna that was clearly (based on isotopic results) gaining the vast majority its energy through chemosynthetic production, and only through clustering analysis was it clear that there was a critical threshold of PUFAs that indicated surface derived versus in situ production. This finding supports the idea that FAs are still pertinent biomarkers to study food webs in chemosynthetic habitats yet understanding their caveats is critical to their implementation. In addition, the application of compound specific fatty acid analysis or amino acid analysis can further resolve any conflicting isotopic and FA data (McClelland & Montoya 2002; Thurber et al. 2012).


  1. Top of page
  2. Abstract
  3. Introduction
  4. Material and Methods
  5. Results
  6. Discussion
  7. Conclusions
  8. Acknowledgements
  9. References

In this paper I have demonstrated that, as Gannes et al. (1997) pointed out, further laboratory studies are still critical to our evaluation of the quantitative nature of food web biomarkers. I have shown that:

  1. Archaeal consumption results in a FA profile indistinct from other food sources;
  2. Unique FA biomarkers from a food source are not always incorporated into consumer tissues and the absence of a biomarker does not indicate a lack of food consumption;
  3. Carbon tissue-diet shifts vary and can be both a function of food source δ13C and C : N ratio;
  4. Δ15N values are variable and sometimes negative.

This study has identified some of the challenges of coupling microbial processes with metazoan diets and highlighted that Bacteria and Archaea are not quantitatively tractable food sources for Ophryotrocha labronica. In addition, this species was able to apparently synthesize essential fatty acids when these FAs were not provided by their food source. Further studies are needed to identify whether the patterns of FA and stable isotope tissue-diet shifts observed in this species are common among other annelid and invertebrate taxa.


  1. Top of page
  2. Abstract
  3. Introduction
  4. Material and Methods
  5. Results
  6. Discussion
  7. Conclusions
  8. Acknowledgements
  9. References

I would like to thank Dr Lisa A. Levin for conceptual input. Dr William Gerwick, Cameron Coates, Jo Nunnery and Dr Tak Suyama provided access to the GC-MS, which was crucial for this study. Dr Emiley Eloe and Dr Douglas Bartlett supplied the cultures of archaeal and bacterial food sources used, without which this study would not have been possible. This paper was improved due to insightful comments by three reviewers. Dr Geoff Cook, Jen Gonzalez and Christina Smith helped with the lab work. Ophryotrocha labronica were kindly provided by Dr Daniella Prevedelli. Support was provided by NSF Grants OCE 0425317, 0826254 and OPP 1103428, the University of California Academic Senate, Michael M. Mullin Memorial Fellowship, University of California Marine Council Coastal Environmental Quality Initiative and Sydney Frank Foundation.


  1. Top of page
  2. Abstract
  3. Introduction
  4. Material and Methods
  5. Results
  6. Discussion
  7. Conclusions
  8. Acknowledgements
  9. References
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