Advertisement

Exometabolomic Mapping of Caenorhabditis elegans: A Tool to Noninvasively Investigate Aging

  • Robert J. Mishur
  • Jeffrey A. Butler
  • Shane L. Rea
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 1048)

Abstract

Metabolomic analyses can provide valuable information about the internal metabolism of an organism; however, these studies can become quickly complicated by the large number of metabolites that are often detected. Overcoming this limitation requires high-resolution analytical separation techniques, coupled with high-power deconvolution software. Additionally, much care must be taken in metabolomic sample preparation to quench active enzymes and avoid artifactual changes in the metabolome. Here we present a relatively simple and straightforward technique, exometabolome mapping, which bypasses each of these concerns, is noninvasive, and provides a concise summary of the key metabolic processes operative in an organism. We illustrate our method using the nematode C. elegans, an organism which has been widely exploited in aging studies; however, with only minimal modification, our technique is extendible to other sample types, and indeed we have successfully used it both to perform yeast footprinting and to study the excreted metabolic end products of human kidney cancer cell lines.

Key words

Metabolomics Metabonomics Aging Exometabolome mapping Caenorhabditis elegans 

Notes

Acknowledgements

The authors gratefully acknowledge Kevin Hakala and Sue Weintraub of the Institutional Mass Spectrometry Laboratory of the University of Texas Health Science Center at San Antonio for their assistance in the development of GC-MS methods. Financial support was provided by the National Institute on Aging (to R.J.M. and S.L.R.) and the Ellison Medical Foundation (S.L.R.).

References

  1. 1.
    Falk MJ, Zhang Z, Rosenjack JR, Nissim I, Daikhin E, Sedensky MM, Yudkoff M, Morgan PG (2008) Metabolic pathway profiling of mitochondrial respiratory chain mutants in C. elegans. Mol Genet Metab 93:388–397. doi: 10.1016/j.ymgme.2007.11.007 PubMedCrossRefGoogle Scholar
  2. 2.
    Rea SL, Graham BH, Nakamaru-Ogiso E, Kar A, Falk MJ (2010) Bacteria, yeast, worms, and flies: exploiting simple model organisms to investigate human mitochondrial diseases. Dev Disabil Res Rev 16:200–218PubMedCrossRefGoogle Scholar
  3. 3.
    Fontana L, Partridge L, Longo VD (2010) Extending healthy life span-from yeast to humans. Science 328:321–326. doi: 10.1126/science.1172539 PubMedCrossRefGoogle Scholar
  4. 4.
    Yuan J, Horvitz HR (1990) The Caenorhabditis elegans genes ced-3 and ced-4 act cell autonomously to cause programmed cell death. Dev Biol 138(1):33–41. doi: 10.1016/0012-1606(90)90174-h PubMedCrossRefGoogle Scholar
  5. 5.
    Liu DW, Thomas JH (1994) Regulation of a periodic motor program in C. elegans. J Neurosci 14:1953–1962PubMedGoogle Scholar
  6. 6.
    Gems D, Riddle DL (2000) Defining wild-type life span in Caenorhabditis elegans. J Gerontol A Biol Sci Med Sci 55(5):B215–B219PubMedCrossRefGoogle Scholar
  7. 7.
    Felkai S, Ewbank JJ, Lemieux J, Labbe JC, Brown GG, Hekimi S (1999) CLK-1 controls respiration, behavior and aging in the nematode Caenorhabditis elegans. EMBO J 18(7):1783–1792. doi: 10.1093/emboj/18.7.1783 PubMedCrossRefGoogle Scholar
  8. 8.
    Lakowski B, Hekimi S (1996) Determination of life-span in Caenorhabditis elegans by four Clock genes. Science 272(5264):1010–1013. doi: 10.1126/science.272.5264.1010 PubMedCrossRefGoogle Scholar
  9. 9.
    Feng J, Bussiere F, Hekimi S (2001) Mitochondrial electron transport is a key determinant of life span in Caenorhabditis elegans. Dev Cell 1(5):633–644. doi: 10.1016/s1534-5807(01)00071-5 PubMedCrossRefGoogle Scholar
  10. 10.
    Yang W, Hekimi S (2010) Two modes of mitochondrial dysfunction lead independently to lifespan extension in Caenorhabditis elegans. Aging Cell 9(3):433–447. doi: 10.1111/j.1474-9726.2010.00571.x PubMedCrossRefGoogle Scholar
  11. 11.
    Iser WB, Wolkow CA (2007) DAF-2/insulin-like signaling in C. elegans modifies effects of dietary restriction and nutrient stress on aging, stress and growth. PLoS One 2(11). doi: 10.1371/journal.pone.0001240
  12. 12.
    Butler JA, Ventura N, Johnson TE, Rea SL (2010) Long-lived mitochondrial (Mit) mutants of Caenorhabditis elegans utilize a novel metabolism. FASEB J 24:4977–4988. doi: 10.1096/fj.10-162941 PubMedCrossRefGoogle Scholar
  13. 13.
    Lakowski B, Hekimi S (1998) The genetics of caloric restriction in Caenorhabditis elegans. Proc Natl Acad Sci U S A 95:13091–13096. doi: 10.1073/pnas.95.22.13091 PubMedCrossRefGoogle Scholar
  14. 14.
    Hiller K, Hangebrauk J, Jager C, Spura J, Schreiber K, Schomburg D (2009) MetaboliteDetector: comprehensive analysis tool for targeted and nontargeted GC/MS based metabolome analysis. Anal Chem 81(9):3429–3439. doi: 10.1021/ac802689c PubMedCrossRefGoogle Scholar
  15. 15.
    Xia J, Psychogios N, Young N, Wishart DS (2009) MetaboAnalyst: a web server for metabolomic data analysis and interpretation. Nucleic Acids Res 37:W652–W660. doi: 10.1093/nar/gkp356 PubMedCrossRefGoogle Scholar
  16. 16.
    Butler JA, Mishur RJ, Bokov AF, Hakala KW, Weintraub ST, Rea SL (2012) Profiling the anaerobic response of C. elegans using GC-MS. PLoS One 7(9):e46140PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, New York 2013

Authors and Affiliations

  • Robert J. Mishur
    • 1
  • Jeffrey A. Butler
    • 1
  • Shane L. Rea
    • 1
  1. 1.Barshop Institute for Longevity and Aging StudiesUniversity of Texas Health Science Center at San AntonioSan AntonioUSA

Personalised recommendations