Predicting elemental cycles and maintaining water quality under increasing anthropogenic influence requires knowledge of the spatial drivers of river microbiomes. However, understanding of the core microbial processes governing river biogeochemistry is hindered by a lack of genome-resolved functional insights and sampling across multiple rivers. Here we used a community science effort to accelerate the sampling, sequencing and genome-resolved analyses of river microbiomes to create the Genome Resolved Open Watersheds database (GROWdb). GROWdb profiles the identity, distribution, function and expression of microbial genomes across river surface waters covering 90% of United States watersheds. Specifically, GROWdb encompasses microbial lineages from 27 phyla, including novel members from 10 families and 128 genera, and defines the core river microbiome at the genome level. GROWdb analyses coupled to extensive geospatial information reveals local and regional drivers of microbial community structuring, while also presenting foundational hypotheses about ecosystem function. Building on the previously conceived River Continuum Concept¹, we layer on microbial functional trait expression, which suggests that the structure and function of river microbiomes is predictable. We make GROWdb available through various collaborative cyberinfrastructures^2,3, so that it can be widely accessed across disciplines for watershed predictive modelling and microbiome-based management practices.

在日益增长的人为影响下预测元素循环和维持水质需要了解河流微生物组的空间驱动因素。然而，由于缺乏基因组分辨的功能见解和跨多条河流的采样，对控制河流生物地球化学的核心微生物过程的理解受到阻碍。在这里，我们利用社区科学工作来加速河流微生物组的采样、测序和基因组分辨分析，以创建基因组分辨开放流域数据库 （GROWdb）。GROWdb 分析了覆盖美国 90% 流域的河流表层水中微生物基因组的身份、分布、功能和表达。具体来说，GROWdb 包含来自 27 个门的微生物谱系，包括来自 10 个科和 128 个属的新成员，并在基因组水平上定义了核心河流微生物组。GROWdb 分析与广泛的地理空间信息相结合，揭示了微生物群落结构的局部和区域驱动因素，同时也提出了有关生态系统功能的基本假设。在先前构想的 River Continuum Concept¹ 的基础上，我们对微生物功能性状表达进行了分层，这表明河流微生物组的结构和功能是可预测的。我们通过各种协作网络基础设施^2,3 提供 GROWdb，以便可以跨学科广泛访问，以进行流域预测建模和基于微生物组的管理实践。