CSIRO Oceans and Atmosphere, Hobart, TAS, Australia.
Ocean Frontier Institute and Department of Oceanography, Dalhousie University, Halifax, NS, Canada.
Nat Commun. 2021 Apr 13;12(1):2213. doi: 10.1038/s41467-021-22409-4.
Global oceanographic monitoring initiatives originally measured abiotic essential ocean variables but are currently incorporating biological and metagenomic sampling programs. There is, however, a large knowledge gap on how to infer bacterial functions, the information sought by biogeochemists, ecologists, and modelers, from the bacterial taxonomic information (produced by bacterial marker gene surveys). Here, we provide a correlative understanding of how a bacterial marker gene (16S rRNA) can be used to infer latitudinal trends for metabolic pathways in global monitoring campaigns. From a transect spanning 7000 km in the South Pacific Ocean we infer ten metabolic pathways from 16S rRNA gene sequences and 11 corresponding metagenome samples, which relate to metabolic processes of primary productivity, temperature-regulated thermodynamic effects, coping strategies for nutrient limitation, energy metabolism, and organic matter degradation. This study demonstrates that low-cost, high-throughput bacterial marker gene data, can be used to infer shifts in the metabolic strategies at the community scale.
全球海洋监测计划最初测量的是无生命的基本海洋变量,但目前正在纳入生物和宏基因组采样计划。然而,如何从细菌分类学信息(通过细菌标记基因调查获得)推断出生物地球化学家、生态学家和模型构建者所寻求的细菌功能信息,这方面仍存在很大的知识空白。在这里,我们提供了一种相关的理解,即如何使用细菌标记基因(16S rRNA)来推断全球监测活动中代谢途径的纬度趋势。从南太平洋跨越 7000 公里的一条横断线上,我们从 16S rRNA 基因序列和 11 个相应的宏基因组样本中推断出十个代谢途径,这些途径与初级生产力的代谢过程、温度调节热力学效应、营养限制的应对策略、能量代谢和有机质降解有关。这项研究表明,低成本、高通量的细菌标记基因数据可用于推断群落尺度上代谢策略的转变。