May. 30, 2018

Stable Isotope Fingerprinting of Amino Acids

A Novel Approach for Tracing Wild and Farmed Salmon

  • Fig. 1: Modern composite aquaculture diets often contain multiple ingredients. The photos are licensed under a Creative Common Attribution 2.0 Generic License. Fig. 1: Modern composite aquaculture diets often contain multiple ingredients. The photos are licensed under a Creative Common Attribution 2.0 Generic License.
  • Fig. 1: Modern composite aquaculture diets often contain multiple ingredients. The photos are licensed under a Creative Common Attribution 2.0 Generic License.
  • Fig. 2: Multivariate analysis of amino acid (AA) d13C values discriminates between different groups of salmon (wild, organic and conventional) with high certainty. Values in parentheses are the percentage variations accounted by each principal components. The first two axes accounting for 80% of variations, separated salmon into distinct groups. The most informative AAs for separating the salmons are four EAAs: histidine (His), leucine (Leu), lysine (Lys) and phenylalanine (Phe) and three NEAAs: asparagine/aspartic acid (Asx), glycine (Gly), and serine (Ser). Figure adapted with permission from [1], copyright Elsevier Publishing
  • Fig. 3: For different feeding experiments, the AA d13C fingerprinting can detect substitution of fishmeal with macroalgae, Palmaria sp. (red algae) and Ulva sp. (green algea), at 5% fishmeal difference relative to their respective control diet groups (algae exclusion diet). For salmon fed 60% insect meal (Insect inclusion), the differences relative to the control group fed on fishmeal and soy proteins (Insect exclusion) were more pronounced. The most informative AAs for separating the salmons from feeding trials are four EAAs: Leu, methionine (Met), proline (Pro), and Phe and three NEAAs: Gly, proline (Pro), Ser and tyrosine (Tyr). Figure adapted with permission from [1], copyright Elsevier Publishing

In a world where food production is becoming more globalized and industrialized, consumers are increasingly concerned about food safety, traceability, and sustainability. This is particularly true for fish and seafood products because more than half of the world’s products now come from aquaculture. To reduce costs and impact on wild fish stocks, carnivorous fish such as salmon and trout are increasingly fed alternatives to fishmeal such as plant- and insect-based diets. However, the rapid development in aquaculture fish production has not been matched by new methods that can accurately trace the food chain supply in aquaculture production. Here we present a novel approach called amino acid δ13C finger-printing that can identify the protein sources of salmon with high accuracy [1].


Although aquaculture is touted as the most efficient method to convert feed to edible protein, the expansion of aquaculture may have significant environmental impacts such as pollution of the environment and reliance on marine feedstuff. To minimize these impacts, more sustainable alternatives to traditional feedstuff are being used and tested [2]. In recent years, commercial compound diets in aquaculture have gone from a single source of protein, fishmeal, and a single source of lipid, fish oil, to more than several dozen ingredients such as soy, insects, macroalgae, mussels and yeast (fig. 1). For example, since 2015 conventionally farmed Atlantic salmon (Salmo salar L.) have been fed only 20% marine based diets as opposed to 90% four decades ago. This diversification in feed ingredients has brought benefits in terms of reduced production costs and has, at least in part, decreased pressure on wild fish stocks. However, up to now new methods that can accurately trace the food chain supply in aquaculture production had been missing.

Amino acid δ13C fingerprinting

We present a novel method, stable isotope fingerprinting of amino acids to authenticate salmons from various geographic locations and sources. Compound-specific isotope analysis (CSIA) of individual amino acids is a rapidly developing tool in ecological and archaeological studies for tracing the origins and fate of nutrients such as the proteinogenic amino acids [2,5], the use of this method in authenticating aquaculture products has until now been largely unexplored.

Amino acids (AA) account for about half of total carbon in most organisms and are therefore among the major conduits of carbon during trophic transfer. Amino acids are excellent source tracer because naturally occurring δ13C variability among AA (δ13CAA) are distinct among major taxonomic groups such as algae, bacteria, fungi and vascular plants [3,6]. These source diagnostic δ13CAA patterns or profiles are also called δ13CAA fingerprints. A distinct advantage of δ13CAA fingerprints over bulk isotopes is that they are minimally affected by shifts in isotope “baselines” among primary production sources [7, 8].

Amino acids can in terms of nutritional requirements be divided into two functional classes: the essential and the non-essential. The AAs that animals cannot synthesis de novo, the essential amino acids (EAAs), are especially suited as dietary tracers because EAAs are directly routed from dietary protein and passed on from food source to consumer without alteration of their carbon skeletons [4]. The non-essential amino acids (NEAA), which are either synthesized by animals de novo or routed directly from dietary sources to tissue [9], can also provide information about diets because they are synthesized from building blocks derived from carbohydrates, lipids and proteins. Taken together, δ13C profiles of both EAA and NEAA are highly promising for authentication of seafood.

Authenticating Salmon

Our study shows that the δ13CAA fingerprinting method has several advantages compared to the prevailing authentication methods because we are able to differentiate organic, conventional, and wild salmon of different origins for the first time (fig. 2). Our method provides far clearer classification boundaries among different salmon groups compared to traditional authentication methods. Also we can distinguish among wild salmon from different geographical regions. Finally, the fingerprints can differentiate between salmon fed alternative diet ingredients such as insect meal and macroalgae (fig. 3). For example, we can detect substitution of fishmeal with macroalgae at 5% protein difference level. The ability of δ13CAA to discriminate between salmon groups can be attributed by the dietary routing of EAA from food sources with unique δ13CEAA fingerprints, and to de novo synthesis of NEAA routed from different dietary components. Our study is the first to fully integrate both the EAA and NEAA as dietary markers.

The ability to detect alternative and subtle diet difference is important for both consumers and the industry because many alternative ingredients can help to decrease environmental impact and improve animal welfare (i.e. by improving the immune system of salmon). Therefore, the industry may soon promote such benefits in their marketing. For example, insect meal was recently approved as an ingredient in the salmon feed by Directorate-General for Health and Food Safety of European Commission (EC, 2017).

Future Work and Perspective

Our method offers a novel and practical solution for the aquaculture industry and other stakeholders (e.g. food standards certifying organizations, environmental advocacy groups, government and its agencies) to authenticate the production origin of salmon and other marine fish species fed complex commercial diets. The new method will help to ensure that sustainable aquaculture products are produced in compliance with standards such as the EU Ecolabel and other organic certification programs and help enhancing food production transparency. Our study primarily serves as a proof-of-concept, and to make the method more widely applicable, it would be necessary to analyze all commercially available feed ingredients to build a reference library.  With further development, the isotope fingerprinting method could support the new blockchain movement for enhancing food safety and production transparency.


The original paper is published in Food Chemistry (doi: 10.1016/j.foodchem.2018.
) [1]. This project was funded by the Cluster of Excellence 80 “The Future Ocean”, a framework of the Excellence Initiative by the Deutsche Forschungsgemeinschaft (DFG) on behalf of the German federal and state governments.

Yiming V. Wang1 and Thomas Larsen1, 2

Dr. Thomas Larsen

Leibniz-Laboratory for Radiometric Dating and Stable Isotope Research,
Christian-Albrechts University of Kiel
Kiel, Germany

1Leibniz-Laboratory for Radiometric Dating and Stable Isotope Research, Christian-Albrechts University of Kiel, Kiel, Germany
2Max Planck Institute for the Science of Human History, Jena, Germany

[1] Y. V. Wang et al., Know your fish: A novel compound-specific isotope approach for tracing wild and farmed salmon. Food Chem 256, 380-389 (2018) doi: 10.1016/j.foodchem.2018.02.095
[2] K. Choy, C. I. Smith, B. T. Fuller, M. P. Richards, Investigation of amino acid d13C signatures in bone collagen to reconstruct human palaeodiets using liquid chromatography-isotope ratio mass spectrometry. Geochimica Et Cosmochimica Acta 74, 6093-6111 (2010)
[3] T. Larsen et al., Tracing Carbon Sources through Aquatic and Terrestrial Food Webs Using Amino Acid Stable Isotope Fingerprinting. Plos One 8, e73441 (2013)
[4] K. W. McMahon, M. L. Fogel, T. S. Elsdon, S. R. Thorrold, Carbon isotope fractionation of amino acids in fish muscle reflects biosynthesis and isotopic routing from dietary protein. Journal of Animal Ecology 79, 1132-1141 (2010)
[5] L. T. Corr, J. C. Sealy, M. C. Horton, R. P. Evershed, A novel marine dietary indicator utilising compound-specific bone collagen amino acid delta C-13 values of ancient humans. Journal of Archaeological Science 32, 321-330 (2005)
[6] T. Larsen, D. L. Taylor, M. B. Leigh, D. M. O'Brien, Stable isotope fingerprinting: a novel method for identifying plant, fungal or bacterial origins of amino acids. Ecology 90, 3526-3535 (2009)
[7] T. Larsen et al., Assessing the potential of amino acid 13C patterns as a carbon source tracer in marine sediments: effects of algal growth conditions and sedimentary diagenesis. Biogeosciences 12, 4979-4992 (2015)
[8] D. M. Post, Using stable isotopes to estimate trophic position: Models, methods, and assumptions. Ecology 83, 703-718 (2002)
[9] J. M. Berg, L. Stryer, J. L. Tymoczko, G. J. Gatto, Biochemistry.  (Macmillan Learning, 2015)

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