Elevated temperature alters proteomic responses of individual organisms within a biofilm community [electronic resource].
- Washington, D.C. : United States. Dept. of Energy, 2014.
Oak Ridge, Tenn. : Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy
- Physical Description:
- pages 180-194 : digital, PDF file
- Additional Creators:
- Oak Ridge National Laboratory, United States. Department of Energy, and United States. Department of Energy. Office of Scientific and Technical Information
- Restrictions on Access:
- Free-to-read Unrestricted online access
- Microbial communities that underpin global biogeochemical cycles will likely be influenced by elevated temperature associated with environmental change. In this paper, we test an approach to measure how elevated temperature impacts the physiology of individual microbial groups in a community context, using a model microbial-based ecosystem. The study is the first application of tandem mass tag (TMT)-based proteomics to a microbial community. We accurately, precisely and reproducibly quantified thousands of proteins in biofilms growing at 40, 43 and 46 °C. Elevated temperature led to upregulation of proteins involved in amino-acid metabolism at the level of individual organisms and the entire community. Proteins from related organisms differed in their relative abundance and functional responses to temperature. Elevated temperature repressed carbon fixation proteins from two Leptospirillum genotypes, whereas carbon fixation proteins were significantly upregulated at higher temperature by a third member of this genus. Leptospirillum group III bacteria may have been subject to viral stress at elevated temperature, which could lead to greater carbon turnover in the microbial food web through the release of viral lysate. Finally, overall, these findings highlight the utility of proteomics-enabled community-based physiology studies, and provide a methodological framework for possible extension to additional mixed culture and environmental sample analyses.
- Report Numbers:
- E 1.99:1286738
- Published through SciTech Connect.
The ISME Journal 9 1 ISSN 1751-7362 AM
Annika C. Mosier; Zhou Li; Brian C. Thomas; Robert L. Hettich; Chongle Pan; Jillian F. Banfield.
- Funding Information:
View MARC record | catkey: 23498861