Department of Plant and Microbial Biology, University of California, Berkeley, California, USA.
Appl Environ Microbiol. 2012 Nov;78(21):7587-95. doi: 10.1128/AEM.00203-12. Epub 2012 Aug 17.
In Mediterranean-type grassland ecosystems, the timing of rainfall events controls biogeochemical cycles, as well as the phenology and productivity of plants and animals. Here, we investigate the effect of short-term (days) soil environmental conditions on microbial community structure and composition during a natural wetting and drying cycle. Soil samples were collected from a meadow in Northern California at four time points after the first two rainfall events of the rainy season. We used 16S rRNA microarrays (PhyloChip) to track changes in bacterial and archaeal community composition. Microbial communities at time points 1 and 3 were significantly different than communities at time points 2 and 4. Based on ordination analysis, the available carbon, soil moisture, and temperature explained most of the variation in community structure. For the first time, a complementary and more comprehensive approach using linear regression and generalized logical networks were used to identify linear and nonlinear associations among environmental variables and with the relative abundance of subfamilies. Changes in soil moisture and available carbon were correlated with the relative abundance of many phyla. Only the phylum Actinobacteria showed a lineage-specific relationship to soil moisture but not to carbon or nitrogen. The results indicate that the use of a high taxonomic rank in correlations with nutritional indicators might obscure divergent subfamily-level responses to environmental parameters. An important implication of this research is that there is short-term variation in microbial community composition driven in part by rainfall fluctuation that may not be evident in long-term studies with coarser time resolution.
在地中海型草原生态系统中,降雨事件的时间控制着生物地球化学循环,以及植物和动物的物候和生产力。在这里,我们研究了短期(几天)土壤环境条件对自然干湿循环过程中微生物群落结构和组成的影响。在雨季的前两次降雨事件之后,我们在加利福尼亚北部的一个草地上采集了四个时间点的土壤样本。我们使用 16S rRNA 微阵列(PhyloChip)来跟踪细菌和古菌群落组成的变化。时间点 1 和 3 的微生物群落与时间点 2 和 4 的群落明显不同。基于排序分析,可用碳、土壤水分和温度解释了群落结构变化的大部分原因。这是首次使用线性回归和广义逻辑网络等补充和更全面的方法,来识别环境变量与相对丰度之间的线性和非线性关联。土壤水分和可用碳的变化与许多门的相对丰度相关。只有放线菌门显示出与土壤水分的谱系特异性关系,但与碳或氮无关。研究结果表明,在与营养指标的相关性中使用较高的分类等级可能会掩盖对环境参数的不同亚家族水平的反应。这项研究的一个重要意义是,微生物群落组成的短期变化部分是由降雨波动驱动的,而在具有较粗时间分辨率的长期研究中可能不明显。