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Refining comparative proteomics by spectral counting to account for shared peptides and multiple search engines

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Abstract

Spectral counting has become a widely used approach for measuring and comparing protein abundance in label-free shotgun proteomics. However, when analyzing complex samples, the ambiguity of matching between peptides and proteins greatly affects the assessment of peptide and protein inventories, differentiation, and quantification. Meanwhile, the configuration of database searching algorithms that assign peptides to MS/MS spectra may produce different results in comparative proteomic analysis. Here, we present three strategies to improve comparative proteomics through spectral counting. We show that comparing spectral counts for peptide groups rather than for protein groups forestalls problems introduced by shared peptides. We demonstrate the advantage and flexibility of this new method in two datasets. We present four models to combine four popular search engines that lead to significant gains in spectral counting differentiation. Among these models, we demonstrate a powerful vote counting model that scales well for multiple search engines. We also show that semi-tryptic searching outperforms tryptic searching for comparative proteomics. Overall, these techniques considerably improve protein differentiation on the basis of spectral count tables.

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Abbreviations

FP:

False positive

MM:

Myrimatch

SQ:

Sequest

TP:

True positive

TR:

TagRecon

XT:

X!Tandem

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Acknowledgments

D. L. Tabb and Y.-Y. Chen were supported by U01 CA152647 from the National Cancer Institute. S. Dasari, Z.-Q. Ma, and L. J. Vega-Montoto were supported by R01 CA126218 from the National Cancer Institute.

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Authors and Affiliations

  1. Department of Biomedical Informatics, Vanderbilt University Medical School, Nashville, TN, 37232-8575, USA

    Yao-Yi Chen, Surendra Dasari, Ze-Qiang Ma, Lorenzo J. Vega-Montoto & David L. Tabb

  2. Division of Cancer Biostatistics, Vanderbilt University Medical School, Nashville, TN, 37232-6848, USA

    Ming Li

Authors
  1. Yao-Yi Chen
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  2. Surendra Dasari
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  3. Ze-Qiang Ma
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  4. Lorenzo J. Vega-Montoto
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  5. Ming Li
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  6. David L. Tabb
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Correspondence to David L. Tabb.

Additional information

Published in the topical issue Quantitative Mass Spectrometry in Proteomics with guest editors Bernhard Kuster and Marcus Bantscheff.

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Chen, YY., Dasari, S., Ma, ZQ. et al. Refining comparative proteomics by spectral counting to account for shared peptides and multiple search engines. Anal Bioanal Chem 404, 1115–1125 (2012). https://doi.org/10.1007/s00216-012-6011-x

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  • DOI: https://doi.org/10.1007/s00216-012-6011-x

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