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Molecular & Cellular Proteomics

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Integrating Global Proteomic and Genomic Expression Profiles Generated from Islet α Cells

Opportunities and Challenges to Deriving Reliable Biological Inferences

Marlena Maziarz, Clement Chung, Daniel J. Drucker and Andrew Emili
Molecular & Cellular Proteomics April 1, 2005, First published on March 1, 2005, 4 (4) 458-474; https://doi.org/10.1074/mcp.R500011-MCP200
Marlena Maziarz
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Clement Chung
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Daniel J. Drucker
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Andrew Emili
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Abstract

Systematic profiling of expressed gene products represents a promising research strategy for elucidating the molecular phenotypes of islet cells. To this end, we have combined complementary genomic and proteomic methods to better assess the molecular composition of murine pancreatic islet glucagon-producing αTC-1 cells as a model system, with the expectation of bypassing limitations inherent to either technology alone. Gene expression was measured with an Affymetrix MG_U74Av2 oligonucleotide array, while protein expression was examined by performing high-resolution gel-free shotgun MS/MS on a nuclear-enriched cell extract. Both analyses were carried out in triplicate to control for experimental variability. Using a stringent detection p value cutoff of 0.04, 48% of all potential mRNA transcripts were predicted to be expressed (probes classified as present in at least two of three replicates), while 1,651 proteins were identified with high-confidence using rigorous database searching. Although 762 of 888 cross-referenced cognate mRNA-protein pairs were jointly detected by both platforms, a sizeable number (126) of gene products was detected exclusively by MS alone. Conversely, marginal protein identifications often had convincing microarray support. Based on these findings, we present an operational framework for both interpreting and integrating dual genomic and proteomic datasets so as to obtain a more reliable perspective into islet α cell function.

Footnotes

  • Published, MCP Papers in Press, March 1, 2005, DOI 10.1074/mcp.R500011-MCP200

  • 1 The abbreviations used are: PM, perfect match; MM, mismatch; MudPIT, multidimensional protein identification technology; RMA, Robust Multichip Average; GO, Gene Ontology; IM, idealized mismatch; ROC, receiver-operating characteristic.

  • 2 M. Maziarz and D. J. Drucker, unpublished observations.

  • 3 P. Hu, personal communication.

  • 4 M. Maziarz, unpublished observations.

  • 5 C. Chung and A. Emili, unpublished observations.

  • 6 Another important form of regulation, reversible posttranslational modification with phosphate, acetyl, glycosyl, or lipid groups, for example, was not addressed in this study

  • ↵* This study was supported by grants from National Science and Engineering Research Council of Canada, Genome Canada, the Ontario Genome Institute, the McLaughlin Centre for Molecular Medicine, and the Ontario Research and Development Challenge Fund (to A. E.), and by an operating grant from the Canadian Institute of Health Research (to D. J. D.). D. J. D. is supported by a Canada Research Chair in Regulatory Peptides.

  • ↵S The on-line version of this manuscript (available at http://www.mcponline.org) contains supplemental material.

  • ↵¶ M. M. and C. C. contributed equally to this study.

    • Received February 25, 2005.
    • Accepted March 1, 2005.
  • The American Society for Biochemistry and Molecular Biology
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Integrating Global Proteomic and Genomic Expression Profiles Generated from Islet α Cells
Marlena Maziarz, Clement Chung, Daniel J. Drucker, Andrew Emili
Molecular & Cellular Proteomics April 1, 2005, First published on March 1, 2005, 4 (4) 458-474; DOI: 10.1074/mcp.R500011-MCP200

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Integrating Global Proteomic and Genomic Expression Profiles Generated from Islet α Cells
Marlena Maziarz, Clement Chung, Daniel J. Drucker, Andrew Emili
Molecular & Cellular Proteomics April 1, 2005, First published on March 1, 2005, 4 (4) 458-474; DOI: 10.1074/mcp.R500011-MCP200
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Molecular & Cellular Proteomics: 4 (4)
Molecular & Cellular Proteomics
Vol. 4, Issue 4
1 Apr 2005
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