MetaProSIP: Automated Inference of Stable Isotope Incorporation Rates in Proteins for Functional Metaproteomics

We propose a joint experimental and theoretical approach to the automated reconstruction of elemental fluxes in microbial communities. While stable isotope probing of proteins (protein-SIP) has been successfully applied to study interactions and elemental carbon and nitrogen fluxes, the volume and c...

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Bibliographic Details
Published in:Journal of proteome research 2015-02, Vol.14 (2), p.619-627
Main Authors: Sachsenberg, Timo, Herbst, Florian-Alexander, Taubert, Martin, Kermer, René, Jehmlich, Nico, von Bergen, Martin, Seifert, Jana, Kohlbacher, Oliver
Format: Article
Language:English
Subjects:
Automation
Isotopes - metabolism
Proteins - metabolism
Proteomics
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Summary:We propose a joint experimental and theoretical approach to the automated reconstruction of elemental fluxes in microbial communities. While stable isotope probing of proteins (protein-SIP) has been successfully applied to study interactions and elemental carbon and nitrogen fluxes, the volume and complexity of mass spectrometric data in protein-SIP experiments pose new challenges for data analysis. Together with a flexible experimental setup, the novel bioinformatics tool MetaProSIP offers an automated high-throughput solution for a wide range of 13C or 15N protein-SIP experiments with special emphasis on the analysis of metaproteomic experiments where differential labeling of organisms can occur. The information calculated in MetaProSIP includes the determination of multiple relative isotopic abundances, the labeling ratio between old and new synthesized proteins, and the shape of the isotopic distribution. These parameters define the metabolic capacities and dynamics within the investigated microbial culture. MetaProSIP features a high degree of reproducibility, reliability, and quality control reporting. The ability to embed into the OpenMS framework allows for flexible construction of custom-tailored workflows. Software and documentation are available under an open-source license at www.openms.de/MetaProSIP.
ISSN:1535-3893
1535-3907
DOI:10.1021/pr500245w