Automating proteome analysis: improvements in throughput, quality and accuracy of protein identification by peptide mass fingerprinting

Authors

  • Ludovic Canelle,

    1. Laboratoire de Biochimie des Protéines et Protéomique, EA 3408, Université Paris 13, UFR SMBH Léonard de Vinci, Bobigny, France
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  • Cédric Pionneau,

    1. Laboratoire de Biochimie des Protéines et Protéomique, EA 3408, Université Paris 13, UFR SMBH Léonard de Vinci, Bobigny, France
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  • Arul Marie,

    1. Laboratoire de Biochimie des Protéines et Protéomique, EA 3408, Université Paris 13, UFR SMBH Léonard de Vinci, Bobigny, France
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  • Jordane Bousquet,

    1. Laboratoire de Biochimie des Protéines et Protéomique, EA 3408, Université Paris 13, UFR SMBH Léonard de Vinci, Bobigny, France
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  • Jean Bigeard,

    1. Laboratoire de Biochimie des Protéines et Protéomique, EA 3408, Université Paris 13, UFR SMBH Léonard de Vinci, Bobigny, France
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  • Didier Lutomski,

    1. Laboratoire de Biochimie des Protéines et Protéomique, EA 3408, Université Paris 13, UFR SMBH Léonard de Vinci, Bobigny, France
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  • Tewfik Kadri,

    1. Laboratoire de Biochimie des Protéines et Protéomique, EA 3408, Université Paris 13, UFR SMBH Léonard de Vinci, Bobigny, France
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  • Michel Caron,

    1. Laboratoire de Biochimie des Protéines et Protéomique, EA 3408, Université Paris 13, UFR SMBH Léonard de Vinci, Bobigny, France
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  • Raymonde Joubert-Caron

    Corresponding author
    1. Laboratoire de Biochimie des Protéines et Protéomique, EA 3408, Université Paris 13, UFR SMBH Léonard de Vinci, Bobigny, France
    • Laboratoire de Biochimie des Protéines et Protéomique, EA 3408, UFR SMBH Léonard de Vinci, 74 rue Marcel Cachin, 93017 Bobigny cedex, France.
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  • These authors contributed equally to this work.

Abstract

The use of robots has major effects on maximizing the proteomic workflow required in an increasing number of high-throughput projects and on increasing the quality of the data. In peptide mass finger printing (PMF), automation of steps downstream of two-dimensional gel electrophoresis is essential. To achieve this goal, the workflow must be fluid. We have developed tools using macros written in Microsoft Excel and Word to complete the automation of our platform. Additionally, because sample preparation is crucial for identification of proteins by matrix-assisted laser desorption/ionization (MALDI) mass spectrometry, we optimized a sandwich method usable by any robot for spotting digests on a MALDI target. This procedure enables further efficient automated washing steps directly on the MALDI target. The success rate of PMF identification was evaluated for the automated sandwich method, and for the dried-droplet method implemented on the robot as recommended by the manufacturer. Of the two methods, the sandwich method achieved the highest identification success rate and sequence coverage of proteins. Copyright © 2004 John Wiley & Sons, Ltd.

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