Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.
Mol Syst Biol. 2011 Mar 15;7:473. doi: 10.1038/msb.2011.6.
Using metagenomic 'parts lists' to infer global patterns on microbial ecology remains a significant challenge. To deduce important ecological indicators such as environmental adaptation, molecular trait dispersal, diversity variation and primary production from the gene pool of an ecosystem, we integrated 25 ocean metagenomes with geographical, meteorological and geophysicochemical data. We find that climatic factors (temperature, sunlight) are the major determinants of the biomolecular repertoire of each sample and the main limiting factor on functional trait dispersal (absence of biogeographic provincialism). Molecular functional richness and diversity show a distinct latitudinal gradient peaking at 20° N and correlate with primary production. The latter can also be predicted from the molecular functional composition of an environmental sample. Together, our results show that the functional community composition derived from metagenomes is an important quantitative readout for molecular trait-based biogeography and ecology.
利用宏基因组“零件清单”来推断微生物生态学的全球模式仍然是一个重大挑战。为了从生态系统的基因库中推断出重要的生态指标,如环境适应性、分子特征传播、多样性变化和初级生产力,我们整合了 25 个海洋宏基因组与地理、气象和地球物理化学数据。我们发现,气候因素(温度、阳光)是每个样本生物分子组成的主要决定因素,也是功能特征传播的主要限制因素(不存在生物地理区域主义)。分子功能丰富度和多样性呈现出明显的纬度梯度,在 20°N 处达到峰值,并与初级生产力相关。后者也可以从环境样本的分子功能组成中预测。总之,我们的研究结果表明,宏基因组衍生的功能群落组成是分子特征为基础的生物地理学和生态学的一个重要定量指标。