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...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:Journal of proteome research Ročník 13; číslo 3; s. 1200
Hlavní autori: 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
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: United States 07.03.2014
Predmet:
ISSN:1535-3907, 1535-3907
On-line prístup:Zistit podrobnosti o prístupe
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Popis
Shrnutí: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.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:1535-3907
1535-3907
DOI:10.1021/pr400633j