Literature DB >> 17928583

Life and death: metabolic rate, membrane composition, and life span of animals.

A J Hulbert1, Reinald Pamplona, Rochelle Buffenstein, W A Buttemer.   

Abstract

Maximum life span differences among animal species exceed life span variation achieved by experimental manipulation by orders of magnitude. The differences in the characteristic maximum life span of species was initially proposed to be due to variation in mass-specific rate of metabolism. This is called the rate-of-living theory of aging and lies at the base of the oxidative-stress theory of aging, currently the most generally accepted explanation of aging. However, the rate-of-living theory of aging while helpful is not completely adequate in explaining the maximum life span. Recently, it has been discovered that the fatty acid composition of cell membranes varies systematically between species, and this underlies the variation in their metabolic rate. When combined with the fact that 1) the products of lipid peroxidation are powerful reactive molecular species, and 2) that fatty acids differ dramatically in their susceptibility to peroxidation, membrane fatty acid composition provides a mechanistic explanation of the variation in maximum life span among animal species. When the connection between metabolic rate and life span was first proposed a century ago, it was not known that membrane composition varies between species. Many of the exceptions to the rate-of-living theory appear explicable when the particular membrane fatty acid composition is considered for each case. Here we review the links between metabolic rate and maximum life span of mammals and birds as well as the linking role of membrane fatty acid composition in determining the maximum life span. The more limited information for ectothermic animals and treatments that extend life span (e.g., caloric restriction) are also reviewed.

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Year:  2007        PMID: 17928583     DOI: 10.1152/physrev.00047.2006

Source DB:  PubMed          Journal:  Physiol Rev        ISSN: 0031-9333            Impact factor:   37.312


  236 in total

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2.  Energy metabolism used as a tool to model the transfer of 14C and 3H in animals.

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3.  Exceptionally old mice are highly resistant to lipoxidation-derived molecular damage.

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Review 4.  Dynamic energy budget approaches for modelling organismal ageing.

Authors:  Ingeborg M M van Leeuwen; Julio Vera; Olaf Wolkenhauer
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2010-11-12       Impact factor: 6.237

Review 5.  Genetic studies reveal the role of the endocrine and metabolic systems in aging.

Authors:  Nir Barzilai; Ilan Gabriely; Gil Atzmon; Yousin Suh; Devorah Rothenberg; Aviv Bergman
Journal:  J Clin Endocrinol Metab       Date:  2010-10       Impact factor: 5.958

Review 6.  Cutting back on the essentials: Can manipulating intake of specific amino acids modulate health and lifespan?

Authors:  Holly M Brown-Borg; Rochelle Buffenstein
Journal:  Ageing Res Rev       Date:  2016-08-26       Impact factor: 10.895

7.  Interspecific correlation between red blood cell mitochondrial ROS production, cardiolipin content and longevity in birds.

Authors:  Jessica Delhaye; Nicolas Salamin; Alexandre Roulin; François Criscuolo; Pierre Bize; Philippe Christe
Journal:  Age (Dordr)       Date:  2016-08-29

8.  Molecular analysis and bioinformatic characterization of cooper, zinc-superoxide dismutase (Cu/Zn-sod) gene of Caiman latirostris.

Authors:  E V Paravani; L M Odetti; M F Simoniello; G L Poletta
Journal:  Mol Biol Rep       Date:  2020-10-31       Impact factor: 2.316

9.  Muscle senescence in short-lived wild mammals, the soricine shrews Blarina brevicauda and Sorex palustris.

Authors:  Allyson G Hindle; John M Lawler; Kevin L Campbell; Markus Horning
Journal:  J Exp Zool A Ecol Genet Physiol       Date:  2009-06-01

10.  Label-free quantitative analysis of lipid metabolism in living Caenorhabditis elegans.

Authors:  Thuc T Le; Holli M Duren; Mikhail N Slipchenko; Chang-Deng Hu; Ji-Xin Cheng
Journal:  J Lipid Res       Date:  2009-09-23       Impact factor: 5.922

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