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      ‘Trophic’ and ‘source’ amino acids in trophic estimation: a likely metabolic explanation

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          Abstract

          Amino acid nitrogen isotopic analysis is a relatively new method for estimating trophic position. It uses the isotopic difference between an individual’s ‘trophic’ and ‘source’ amino acids to determine its trophic position. So far, there is no accepted explanation for the mechanism by which the isotopic signals in ‘trophic’ and ‘source’ amino acids arise. Yet without a metabolic understanding, the utility of nitrogen isotopic analyses as a method for probing trophic relations, at either bulk tissue or amino acid level, is limited. I draw on isotopic tracer studies of protein metabolism, together with a consideration of amino acid metabolic pathways, to suggest that the ‘trophic’/‘source’ groupings have a fundamental metabolic origin, to do with the cycling of amino-nitrogen between amino acids. ‘Trophic’ amino acids are those whose amino-nitrogens are interchangeable, part of a metabolic amino-nitrogen pool, and ‘source’ amino acids are those whose amino-nitrogens are not interchangeable with the metabolic pool. Nitrogen isotopic values of ‘trophic’ amino acids will reflect an averaged isotopic signal of all such dietary amino acids, offset by the integrated effect of isotopic fractionation from nitrogen cycling, and modulated by metabolic and physiological effects. Isotopic values of ‘source’ amino acids will be more closely linked to those of equivalent dietary amino acids, but also modulated by metabolism and physiology. The complexity of nitrogen cycling suggests that a single identifiable value for ‘trophic discrimination factors’ is unlikely to exist. Greater consideration of physiology and metabolism should help in better understanding observed patterns in nitrogen isotopic values.

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          The large-scale organization of metabolic networks

          In a cell or microorganism the processes that generate mass, energy, information transfer, and cell fate specification are seamlessly integrated through a complex network of various cellular constituents and reactions. However, despite the key role these networks play in sustaining various cellular functions, their large-scale structure is essentially unknown. Here we present the first systematic comparative mathematical analysis of the metabolic networks of 43 organisms representing all three domains of life. We show that, despite significant variances in their individual constituents and pathways, these metabolic networks display the same topologic scaling properties demonstrating striking similarities to the inherent organization of complex non-biological systems. This suggests that the metabolic organization is not only identical for all living organisms, but complies with the design principles of robust and error-tolerant scale-free networks, and may represent a common blueprint for the large-scale organization of interactions among all cellular constituents.
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            The small world inside large metabolic networks.

            The metabolic network of the catabolic, energy and biosynthetic metabolism of Escherichia coli is a paradigmatic case for the large genetic and metabolic networks that functional genomics efforts are beginning to elucidate. To analyse the structure of previously unknown networks involving hundreds or thousands of components by simple visual inspection is impossible, and quantitative approaches are needed to analyse them. We have undertaken a graph theoretical analysis of the E. coli metabolic network and find that this network is a small-world graph, a type of graph distinct from both regular and random networks and observed in a variety of seemingly unrelated areas, such as friendship networks in sociology, the structure of electrical power grids, and the nervous system of Caenorhabditis elegans. Moreover, the connectivity of the metabolites follows a power law, another unusual but by no means rare statistical distribution. This provides an objective criterion for the centrality of the tricarboxylic acid cycle to metabolism. The small-world architecture may serve to minimize transition times between metabolic states, and contains evidence about the evolutionary history of metabolism.
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              Resolving temporal variation in vertebrate diets using naturally occurring stable isotopes.

              Assessments of temporal variation in diets are important for our understanding of the ecology of many vertebrates. Ratios of naturally occurring stable isotopes in animal tissues are a combination of the source elements and tissue specific fractionation processes, and can thus reveal dietary information. We review three different approaches that have been used to resolve temporal diet variation through analysis of stable isotopes. The most straightforward approach is to compare samples from the same type of tissue that has been sampled over time. This approach is suited to address either long or short-term dietary variation, depending on sample regime and which tissue that is sampled. Second, one can compare tissues with different metabolic rates. Since the elements in a given tissue have been assimilating during time spans specific to its metabolic rate, tissues with different metabolic rates will reflect dietary records over different periods. Third, comparisons of sections from tissues with progressive growth, such as hair, feathers, claws and teeth, will reveal temporal variation since these tissues will retain isotopic values in a chronological order. These latter two approaches are mainly suited to address questions regarding intermediate and short-term dietary variation. Knowledge of tissue specific metabolic rates, which determine the molecular turnover for a specific tissue, is of central importance for all these comparisons. Estimates of isotopic fractionation between source and measured target are important if specific hypotheses regarding the source elements are addressed. Estimates of isotopic fractionation, or at least of differences in fractionation between tissues, are necessary if different tissues are compared. We urge for more laboratory experiments aimed at improving our understanding of differential assimilation of dietary components, isotopic fractionation and metabolic routing. We further encourage more studies on reptiles and amphibians, and generally more studies utilizing multiple tissues with different turnover rates.
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                Author and article information

                Contributors
                +44-1223-339344 , tco21@cam.ac.uk
                Journal
                Oecologia
                Oecologia
                Oecologia
                Springer Berlin Heidelberg (Berlin/Heidelberg )
                0029-8549
                1432-1939
                6 June 2017
                6 June 2017
                2017
                : 184
                : 2
                : 317-326
                Affiliations
                ISNI 0000000121885934, GRID grid.5335.0, Department of Archaeology and Anthropology, , University of Cambridge, ; Downing Street, Cambridge, CB2 3DZ UK
                Author notes

                Communicated by Blair Wolf.

                Article
                3881
                10.1007/s00442-017-3881-9
                5487837
                28584941
                76090237-9bd1-439f-9a40-1e820bc9aecf
                © The Author(s) 2017

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

                History
                : 27 July 2016
                : 8 May 2017
                Categories
                Concepts, Reviews and Syntheses
                Custom metadata
                © Springer-Verlag GmbH Germany 2017

                Ecology
                nitrogen isotopic analysis,isotope,metabolism,trophic discrimination factor,trophic enrichment factor,food web

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