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A practical guide to the MaxQuant computational platform for SILAC-based quantitative proteomics

Nature Protocols volume 4, pages 698–705 (2009)Cite this article

Abstract

MaxQuant is a quantitative proteomics software package designed for analyzing large mass spectrometric data sets. It is specifically aimed at high-resolution mass spectrometry (MS) data. Currently, Thermo LTQ-Orbitrap and LTQ-FT-ICR instruments are supported and Mascot is used as a search engine. This protocol explains step by step how to use MaxQuant on stable isotope labeling by amino acids in cell culture (SILAC) data obtained with double or triple labeling. Complex experimental designs, such as time series and drug-response data, are supported. A standard desktop computer is sufficient to fulfill the computational requirements. The workflow has been stress tested with more than 1,000 liquid chromatography/mass spectrometry runs in a single project. In a typical SILAC proteome experiment, hundreds of thousands of peptides and thousands of proteins are automatically and reliably quantified. Additional information for identified proteins, such as Gene Ontology, domain composition and pathway membership, is provided in the output tables ready for further bioinformatics analysis. The software is freely available at the MaxQuant home page.

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Figure 1: Overview of the computational workflow.
Figure 2: The graphical user interface of the Quant module.
Figure 3: The graphical user interface of the Identify module.

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Acknowledgements

We thank all the other members of the Proteomics and Signal Transduction group for help with the development of MaxQuant. This work was supported by the Max-Planck Society and by the 6th Framework Program of the European Union (Interaction Proteome Grant LSHG-CT-2003-505520 and HEROIC Grant LSHG-CT-2005-018883).

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Authors and Affiliations

  1. Department for Proteomics and Signal Transduction, Max-Planck Institute for Biochemistry, Martinsried, Germany

    Jürgen Cox, Ivan Matic, Maximiliane Hilger, Nagarjuna Nagaraj, Jesper V Olsen & Matthias Mann

  2. Department for Cell Signalling and Mass Spectrometry, Max Delbrück Center for Molecular Medicine, Berlin, Germany

    Matthias Selbach

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  1. Jürgen Cox
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  2. Ivan Matic
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  3. Maximiliane Hilger
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  7. Matthias Mann
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Correspondence to Jürgen Cox or Matthias Mann.

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Cox, J., Matic, I., Hilger, M. et al. A practical guide to the MaxQuant computational platform for SILAC-based quantitative proteomics. Nat Protoc 4, 698–705 (2009). https://doi.org/10.1038/nprot.2009.36

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