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

Gordon W. Slysz, Laurey Steinke, David M. Ward, Christian G. Klatt, Therese R W Clauss, Samuel O. Purvine, Samuel H. Payne, Gordon A. Anderson, Richard D. Smith, Mary S. Lipton

Research output: Contribution to journalArticlepeer-review

17 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)1200-1210
Number of pages11
JournalJournal of proteome research
Issue number3
StatePublished - Mar 7 2014


  • C labeling
  • bioinformatics
  • carbon metabolism
  • metaproteomics
  • proteomics
  • stable isotope probing

ASJC Scopus subject areas

  • Biochemistry
  • Chemistry(all)


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