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|Abstract:||Connecting molecular information directly to microbial transformation rates remains a challenge, despite the availability of molecular methods to investigate microbial biogeochemistry. By combining information on gene abundance and expression for key genes with quantitative modeling of nitrogen fluxes, we can begin to understand the scales on which genetic signals vary and how they relate to key functions. We used quantitative PCR of DNA and cDNA, along with biogeochemical modeling to assess how the abundance and expression of microbes responsible for two steps in the nitrogen cycle changed over time in estuarine sediment mesocosms. Sediments and water were collected from coastal Massachusetts and maintained in replicated 20 L mesocosms for 45 days. Concentrations of all major inorganic nitrogen species were measured daily and used to derive rates of nitrification and denitrification from a Monte Carlo-based non-negative least-squares analysis of finite difference equations. The mesocosms followed a classic regeneration sequence in which ammonium released from the decomposition of organic matter was subsequently oxidized to nitrite and then further to nitrate, some portion of which was ultimately denitrified. Normalized abundances of ammonia oxidizing archaeal ammonia monoxoygenase (amoA) transcripts closely tracked rates of ammonia oxidation throughout the experiment. No such relationship, however, was evident between denitrification rates and the normalized abundance of nitrite reductase (nirS and nirK) transcripts. These findings underscore the complexity of directly linking the structure of the microbial community to rates of biogeochemical processes.|
|Citation:||Bowen, Jennifer L., Andrew R. Babbin, Patrick J. Kearns, and Bess B. Ward. "Connecting the dots: linking nitrogen cycle gene expression to nitrogen fluxes in marine sediment mesocosms." Frontiers in Microbiology 5 (2014). doi:10.3389/fmicb.2014.00429.|
|Type of Material:||Journal Article|
|Journal/Proceeding Title:||Frontiers in Microbiology|
|Version:||Final published version. This is an open access article.|
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