Meta-analysis of global metabolomics and proteomics data to link alterations with phenotype

Patti, Gary J.; Tautenhahn, Ralf; Fonslow, Bryan R.; Cho, Yonghoon; Deutschbauer, Adam; Arkin, Adam; Northen, Trent; Siuzdak, Gary

doi:10.1155/2011/923017

Title: Meta-analysis of global metabolomics and proteomics data to link alterations with phenotype

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Abstract

Global metabolomics has emerged as a powerful tool to interrogate cellular biochemistry at the systems level by tracking alterations in the levels of small molecules. One approach to define cellular dynamics with respect to this dysregulation of small molecules has been to consider metabolic flux as a function of time. While flux measurements have proven effective for model organisms, acquiring multiple time points at appropriate temporal intervals for many sample types (e.g., clinical specimens) is challenging. As an alternative, meta-analysis provides another strategy for delineating metabolic cause and effect perturbations. That is, the combination of untargeted metabolomic data from multiple pairwise comparisons enables the association of specific changes in small molecules with unique phenotypic alterations. We recently developed metabolomic software called metaXCMS to automate these types of higher order comparisons. Here we discuss the potential of metaXCMS for analyzing proteomic datasets and highlight the biological value of combining meta-results from both metabolomic and proteomic analyses. The combined meta-analysis has the potential to facilitate efforts in functional genomics and the identification of metabolic disruptions related to disease pathogenesis.

Authors:

Patti, Gary J. ^[1]; Tautenhahn, Ralf ^[2]; Fonslow, Bryan R. ^[3]; Cho, Yonghoon ^[2]; Deutschbauer, Adam ^[4]; Arkin, Adam ^[4]; Northen, Trent ^[5]; Siuzdak, Gary ^[2]

Departments of Chemistry, Genetics and Medicine, Washington University School of Medicine, St. Louis, MO, USA
Center for Metabolomics and Mass Spectrometry, The Scripps Research Institute, La Jolla, CA, USA
Department of Chemical Physiology, The Scripps Research Institute, La Jolla, CA, USA
Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
Department of Bioengergy/GTL & Structural Biology, Life Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA

Publication Date:: Sat Jan 01 00:00:00 EST 2011

Sponsoring Org.:: USDOE

OSTI Identifier:: 1227978

Grant/Contract Number:: ENIGMA DE-AC0205CH11231

Resource Type:: Published Article

Journal Name:: Spectroscopy

Additional Journal Information:: Journal Name: Spectroscopy Journal Volume: 26 Journal Issue: 3; Journal ID: ISSN 0712-4813

Publisher:: Hindawi Publishing Corporation

Country of Publication:: Country unknown/Code not available

Language:: English

Citation Formats


                    Patti, Gary J., Tautenhahn, Ralf, Fonslow, Bryan R., Cho, Yonghoon, Deutschbauer, Adam, Arkin, Adam, Northen, Trent, and Siuzdak, Gary. Meta-analysis of global metabolomics and proteomics data to link alterations with phenotype.  Country unknown/Code not available: N. p., 2011. 
Web.  doi:10.1155/2011/923017.

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                    Patti, Gary J., Tautenhahn, Ralf, Fonslow, Bryan R., Cho, Yonghoon, Deutschbauer, Adam, Arkin, Adam, Northen, Trent, & Siuzdak, Gary. Meta-analysis of global metabolomics and proteomics data to link alterations with phenotype.  Country unknown/Code not available.  https://doi.org/10.1155/2011/923017

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                    Patti, Gary J., Tautenhahn, Ralf, Fonslow, Bryan R., Cho, Yonghoon, Deutschbauer, Adam, Arkin, Adam, Northen, Trent, and Siuzdak, Gary. Sat .  
"Meta-analysis of global metabolomics and proteomics data to link alterations with phenotype".  Country unknown/Code not available.  https://doi.org/10.1155/2011/923017.

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@article{osti_1227978,

  title        = {Meta-analysis of global metabolomics and proteomics data to link alterations with phenotype},

  author       = {Patti, Gary J. and Tautenhahn, Ralf and Fonslow, Bryan R. and Cho, Yonghoon and Deutschbauer, Adam and Arkin, Adam and Northen, Trent and Siuzdak, Gary},

  abstractNote = {Global metabolomics has emerged as a powerful tool to interrogate cellular biochemistry at the systems level by tracking alterations in the levels of small molecules. One approach to define cellular dynamics with respect to this dysregulation of small molecules has been to consider metabolic flux as a function of time. While flux measurements have proven effective for model organisms, acquiring multiple time points at appropriate temporal intervals for many sample types (e.g., clinical specimens) is challenging. As an alternative, meta-analysis provides another strategy for delineating metabolic cause and effect perturbations. That is, the combination of untargeted metabolomic data from multiple pairwise comparisons enables the association of specific changes in small molecules with unique phenotypic alterations. We recently developed metabolomic software called metaXCMS to automate these types of higher order comparisons. Here we discuss the potential of metaXCMS for analyzing proteomic datasets and highlight the biological value of combining meta-results from both metabolomic and proteomic analyses. The combined meta-analysis has the potential to facilitate efforts in functional genomics and the identification of metabolic disruptions related to disease pathogenesis.},

  doi          = {10.1155/2011/923017},

  journal      = {Spectroscopy},

  number       = 3,

  volume       = 26,

  place        = {Country unknown/Code not available},

  year         = {Sat Jan 01 00:00:00 EST 2011},

  month        = {Sat Jan 01 00:00:00 EST 2011}

}

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