Functional gene arrays (FGAs), such as GeoChip, which contain key genes encoding functional enzymes involved in biogeochemical cycling, have been successfully used for tracking and studying the biogeochemical processes in different
ecosystems, including groundwater and aquatic ecosystems, soil, extreme environments, bioreactor systems, and oil-contaminated waters or soils [18, 19]. Combined with multivariate statistical analyses , several systematic experimental evaluations have indicated that GeoChip can be used as a specific, sensitive tool for detecting the functional diversity, composition, structure, and metabolic potential of microbial communities, and correlating Vorinostat molecular weight microbial selleckchem communities to ecosystem processes and functioning [21–24]. We hypothesized that
soil microbial community composition and structure would be altered directly or indirectly by eCO2, and that the BMN673 functional gene groups involved in C and N cycling would be enhanced due to the increase of soil C input under eCO2. To test those hypotheses, we conducted our experiments at the Cedar Creek Ecosystem Science Reserve in Minnesota (http://www.biocon.umn.edu/). A comprehensive functional gene array, GeoChip 3.0 , was used to analyze the function composition and structure of soil microbial communities under both ambient and elevated CO2 concentrations. Some key genes involved in C and N cycling were stimulated under
CO2. This study provides new information for our understanding of the feedback response of soil microbial 4-Aminobutyrate aminotransferase communities to eCO2. Results Overall responses of microbial C and N cycling genes under CO2 Based on the number of functional genes, Shannon diversity, evenness and dominance, no significant differences were detected in the overall microbial diversity (Additional file 1). Significant (p < 0.05) differences were observed in the abundance of C and N cycling genes between ambient CO2 (aCO2) and eCO2 microbial communities by detrended correspondence analysis (DCA) together with analysis of similarities (ANOSIM), non-parametric multivariate analysis of variance (Adonis) and Multi-Response Permutation Procedure (MRPP). The eCO2 samples were well separated from aCO2 ones by the first axis of DCA, which explained 10.4% and 10.1% for the genes involved in C cycling (Figure 1A) and N cycling (Figure 1B), respectively. These results suggest that most of the functional genes involved in C and N cycling were significantly stimulated, and that the functional composition and structure of soil microbial communities were also altered at eCO2. More details about individual key C and N cycling genes and their associated populations are described below. Figure 1 Detrended correspondence analysis (DCA) of the samples under ambient and elevated CO 2 bsed on GeoChip 3. 0 data of the genes involved in carbon (A) and nitrogen (B) cycling.