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Effect of Fasting on the Metabolic Response of Liver to Experimental Burn Injury

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      Abstract

      Liver metabolism is altered after systemic injuries such as burns and trauma. These changes have been elucidated in rat models of experimental burn injury where the liver was isolated and perfused ex vivo. Because these studies were performed in fasted animals to deplete glycogen stores, thus simplifying quantification of gluconeogenesis, these observations reflect the combined impact of fasting and injury on liver metabolism. Herein we asked whether the metabolic response to experimental burn injury is different in fed vs. fasted animals. Rats were subjected to a cutaneous burn covering 20% of the total body surface area, or to similar procedures without administering the burn, hence a sham-burn. Half of the animals in the burn and sham-burn groups were fasted starting on postburn day 3, and the others allowed to continue ad libitum. On postburn day 4, livers were isolated and perfused for 1 hour in physiological medium supplemented with 10% hematocrit red blood cells. The uptake/release rates of major carbon and nitrogen sources, oxygen, and carbon dioxide were measured during the perfusion and the data fed into a mass balance model to estimate intracellular fluxes. The data show that in fed animals, injury increased glucose output mainly from glycogen breakdown and minimally impacted amino acid metabolism. In fasted animals, injury did not increase glucose output but increased urea production and the uptake of several amino acids, namely glutamine, arginine, glycine, and methionine. Furthermore, sham-burn animals responded to fasting by triggering gluconeogenesis from lactate; however, in burned animals the preferred gluconeogenic substrate was amino acids. Taken together, these results suggest that the fed state prevents the burn-induced increase in hepatic amino acid utilization for gluconeogenesis. The role of glycogen stores and means to increase and/or maintain internal sources of glucose to prevent increased hepatic amino acid utilization warrant further studies.

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      Structural and functional analysis of cellular networks with CellNetAnalyzer

      Background Mathematical modelling of cellular networks is an integral part of Systems Biology and requires appropriate software tools. An important class of methods in Systems Biology deals with structural or topological (parameter-free) analysis of cellular networks. So far, software tools providing such methods for both mass-flow (metabolic) as well as signal-flow (signalling and regulatory) networks are lacking. Results Herein we introduce CellNetAnalyzer, a toolbox for MATLAB facilitating, in an interactive and visual manner, a comprehensive structural analysis of metabolic, signalling and regulatory networks. The particular strengths of CellNetAnalyzer are methods for functional network analysis, i.e. for characterising functional states, for detecting functional dependencies, for identifying intervention strategies, or for giving qualitative predictions on the effects of perturbations. CellNetAnalyzer extends its predecessor FluxAnalyzer (originally developed for metabolic network and pathway analysis) by a new modelling framework for examining signal-flow networks. Two of the novel methods implemented in CellNetAnalyzer are discussed in more detail regarding algorithmic issues and applications: the computation and analysis (i) of shortest positive and shortest negative paths and circuits in interaction graphs and (ii) of minimal intervention sets in logical networks. Conclusion CellNetAnalyzer provides a single suite to perform structural and qualitative analysis of both mass-flow- and signal-flow-based cellular networks in a user-friendly environment. It provides a large toolbox with various, partially unique, functions and algorithms for functional network analysis.CellNetAnalyzer is freely available for academic use.
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        Alterations in carbohydrate metabolism during stress: a review of the literature.

        Patients with sepsis, burn, or trauma commonly enter a hypermetabolic stress state that is associated with a number of alterations in carbohydrate metabolism. These alterations include enhanced peripheral glucose uptake and utilization, hyperlactatemia, increased glucose production, depressed glycogenesis, glucose intolerance, and insulin resistance. The hypermetabolic state is induced by the area of infection or injury as well as by organs involved in the immunologic response to stress; it generates a glycemic milieu that is directed toward satisfying an obligatory requirement for glucose as an energy substrate. This article reviews experimental and clinical data that indicate potential mechanisms for these alterations and emphasizes aspects that have relevance for the clinician.
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          Support of the metabolic response to burn injury.

          Severe burn causes metabolic disturbances that can last for a year after injury; persistent and profound catabolism hampers rehabilitative efforts and delays the meaningful return of individuals to society. The simplest, effective anabolic strategies for severe burn injuries are: early excision and grafting of the wound; prompt treatment of sepsis; maintenance of environmental temperature at 30-32 degrees C; continuous feeding of a high carbohydrate, high protein diet, preferably by the enteral route; and early institution of vigorous and aerobic resistive exercise programmes. To further keep erosion of lean body mass to a minimum, administration of anabolic agents, recombinant human growth hormone, insulin, oxandrolone, or anticatabolic drugs such as propranolol are alternative approaches. Exogenous continuous low-dose insulin infusion, beta blockade with propranolol, and use of the synthetic testosterone analogue oxandrolone are the most cost effective and least toxic pharmacological treatments to date.
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            Author and article information

            Affiliations
            [1 ]Department of Chemical and Biochemical Engineering, Rutgers, The State University of New Jersey, Piscataway, New Jersey, United States of America
            [2 ]Department of Biomedical Engineering, Rutgers, The State University of New Jersey, Piscataway, New Jersey, United States of America
            Michigan State University, United States of America
            Author notes

            Competing Interests: The authors have declared that no competing interests exist.

            Conceived and designed the experiments: MAO MGI IPA FB. Performed the experiments: MAO. Analyzed the data: MAO MGI IPA FB. Contributed reagents/materials/analysis tools: MGI IPA FB. Wrote the paper: MAO MGI IPA FB.

            Contributors
            Role: Editor
            Journal
            PLoS One
            PLoS ONE
            plos
            plosone
            PLoS ONE
            Public Library of Science (San Francisco, USA )
            1932-6203
            2013
            5 February 2013
            : 8
            : 2
            23393558
            3564862
            PONE-D-12-23894
            10.1371/journal.pone.0054825
            (Editor)

            This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

            Counts
            Pages: 15
            Funding
            The authors gratefully acknowledge the financial support from National Institutes of Health grant GM082974. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
            Categories
            Research Article
            Biology
            Biochemistry
            Bioenergetics
            Energy-Producing Processes
            Enzymes
            Enzyme Metabolism
            Metabolism
            Carbohydrate Metabolism
            Lipid Metabolism
            Metabolic Pathways
            Nitrogen Metabolism
            Oxygen Metabolism
            Computational Biology
            Metabolic Networks
            Engineering
            Bioengineering
            Biological Systems Engineering
            Biomedical Engineering

            Uncategorized

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