Automated data extraction from in situ protein-stable isotope probing studies

Protein-stable isotope probing (protein-SIP) has strong potential for revealing key metabolizing taxa in complex microbial communities. While most protein-SIP work to date has been performed under controlled laboratory conditions to allow extensive isotope labeling of the target organism(s), a key a...

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Veröffentlicht in:Journal of proteome research Jg. 13; H. 3; S. 1200
Hauptverfasser: Slysz, Gordon W, Steinke, Laurey, Ward, David M, Klatt, Christian G, Clauss, Therese R W, Purvine, Samuel O, Payne, Samuel H, Anderson, Gordon A, Smith, Richard D, Lipton, Mary S
Format: Journal Article
Sprache:Englisch
Veröffentlicht: United States 07.03.2014
Schlagworte:
Amino Acid Sequence
Bacterial Proteins - analysis
Bacterial Proteins - genetics
Bacterial Proteins - metabolism
Carbon Isotopes
Computational Biology
Data Mining
Gene Expression
Isotope Labeling
Microbial Consortia - genetics
Molecular Sequence Data
Nitrogen Isotopes
Phototrophic Processes
Proteome - analysis
Proteome - genetics
Proteome - metabolism
Software
ISSN:1535-3907, 1535-3907
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Zusammenfassung:Protein-stable isotope probing (protein-SIP) has strong potential for revealing key metabolizing taxa in complex microbial communities. While most protein-SIP work to date has been performed under controlled laboratory conditions to allow extensive isotope labeling of the target organism(s), a key application will be in situ studies of microbial communities for short periods of time under natural conditions that result in small degrees of partial labeling. One hurdle restricting large-scale in situ protein-SIP studies is the lack of algorithms and software for automated data processing of the massive data sets resulting from such studies. In response, we developed Stable Isotope Probing Protein Extraction Resources software (SIPPER) and applied it for large-scale extraction and visualization of data from short-term (3 h) protein-SIP experiments performed in situ on phototrophic bacterial mats isolated from Yellowstone National Park. Several metrics incorporated into the software allow it to support exhaustive analysis of the complex composite isotopic envelope observed as a result of low amounts of partial label incorporation. SIPPER also enables the detection of labeled molecular species without the need for any prior identification.
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ISSN:1535-3907
1535-3907
DOI:10.1021/pr400633j