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Meta-Proteome-Analyzer: A software tool specifically developed for the functional and taxonomic characterization of metaproteome data.

MPS-Authors

Muth,  Thilo
Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons86324

Heyer,  Robert
Bioprocess Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;

Behne,  A.
Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons96212

Kohrs,  Fabian
Bioprocess Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons86252

Benndorf,  Dirk
Bioprocess Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons86442

Rapp,  Erdmann
Bioprocess Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons86448

Reichl,  Udo
Otto-von-Guericke-Universität Magdeburg;
Bioprocess Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;

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Citation

Muth, T., Heyer, R., Behne, A., Kohrs, F., Benndorf, D., Rapp, E., et al. (2012). Meta-Proteome-Analyzer: A software tool specifically developed for the functional and taxonomic characterization of metaproteome data. Poster presented at GCB2012: German conference on bioinformatics, Jena, Germany.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0013-8880-7
Abstract
The functional analysis of highly complex microbial communities is a rather challenging discipline in proteomics. However, there is no alternative to its use if biological measures are required to improve the economic efficiency of biogas plants and waste water treatment plants, to remediate contaminated soil and water or to investigate the complex interactions in the human gut. Currently, analysis and interpretation of data derived from LC-MS/MS experiments present a major bottleneck in metaproteomics. In contrast to pure-culture proteomics, metaproteome samples are heterogeneous and much more complex. Moreover, for the major part of the microorganisms, protein sequence information is not available which results in a low protein identification rate. To overcome limits of existing solutions, we developed a software tool for the functional and taxonomic characterization of metaproteomics data we called MetaProteomeAnalyzer (MPA). Beside an advanced protein identification by a combination of multiple database search algorithms (Crux, OMSSA, X!Tandem, Inspect), and a spectral library search, the identification of proteins from unsequenced species by de novo sequencing and a BLAST search are included in the workflow. In addition, features for the analysis of the taxonomic diversity of a microbial community and for the functional classification of proteins are included.MPA constitutes a protein identification platform specialized on metaproteomics, which facilitates the analysis of complex microbial communities and increases significantly the number of identified proteins.