Department of Ecology and Evolutionary Biology, University of Colorado, Boulder, Colorado, USA.
Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, Colorado, USA.
mSystems. 2022 Oct 26;7(5):e0065122. doi: 10.1128/msystems.00651-22. Epub 2022 Sep 19.
Wastewater microbial communities are not static and can vary significantly across time and space, but this variation and the factors driving the observed spatiotemporal variation often remain undetermined. We used a shotgun metagenomic approach to investigate changes in wastewater microbial communities across 17 locations in a sewer network, with samples collected from each location over a 3-week period. Fecal material-derived bacteria constituted a relatively small fraction of the taxa found in the collected samples, highlighting the importance of environmental sources to the sewage microbiome. The prokaryotic communities were highly variable in composition depending on the location within the sampling network, and this spatial variation was most strongly associated with location-specific differences in sewage pH. However, we also observed substantial temporal variation in the composition of the prokaryotic communities at individual locations. This temporal variation was asynchronous across sampling locations, emphasizing the importance of independently considering both spatial and temporal variation when assessing the wastewater microbiome. The spatiotemporal patterns in viral community composition closely tracked those of the prokaryotic communities, allowing us to putatively identify the bacterial hosts of some of the dominant viruses in these systems. Finally, we found that antibiotic resistance gene profiles also exhibit a high degree of spatiotemporal variability, with most of these genes unlikely to be derived from fecal bacteria. Together, these results emphasize the dynamic nature of the wastewater microbiome, the challenges associated with studying these systems, and the utility of metagenomic approaches for building a multifaceted understanding of these microbial communities and their functional attributes. Sewage systems harbor extensive microbial diversity, including microbes derived from both human and environmental sources. Studies of the sewage microbiome are useful for monitoring public health and the health of our infrastructure, but the sewage microbiome can be highly variable in ways that are often unresolved. We sequenced DNA recovered from wastewater samples collected over a 3-week period at 17 locations in a single sewer system to determine how these communities vary across time and space. Most of the wastewater bacteria, and the antibiotic resistance genes they harbor, were not derived from human feces, but human usage patterns did impact how the amounts and types of bacteria and bacterial genes we found in these systems varied over time. Likewise, the wastewater communities, including both bacteria and their viruses, varied depending on location within the sewage network, highlighting the challenges and opportunities in efforts to monitor and understand the sewage microbiome.
污水微生物群落并非静态的,它们会随时间和空间发生显著变化,但这种变化以及导致观察到的时空变化的因素通常仍未确定。我们使用高通量宏基因组学方法研究了污水微生物群落在污水管网 17 个位置的变化,每个位置的样本在 3 周内采集一次。从每个位置采集的样本中,粪便来源的细菌仅构成了所发现的分类群的一小部分,这突出了环境来源对污水微生物组的重要性。原核生物群落的组成在很大程度上取决于采样网络中的位置,这种空间变化与特定位置污水 pH 值的差异密切相关。然而,我们还观察到个别位置的原核生物群落组成也存在很大的时间变化。这种时间变化在采样位置之间是不同步的,这强调了在评估污水微生物组时,同时考虑空间和时间变化的重要性。病毒群落组成的时空模式与原核生物群落的模式密切相关,这使我们能够推测出这些系统中一些优势病毒的细菌宿主。最后,我们发现抗生素耐药基因谱也表现出高度的时空变异性,其中大多数基因不太可能来自粪便细菌。综上所述,这些结果强调了污水微生物组的动态性质,研究这些系统所面临的挑战,以及宏基因组学方法在构建对这些微生物群落及其功能属性的多方面理解方面的实用性。污水系统中蕴藏着广泛的微生物多样性,包括来自人类和环境来源的微生物。对污水微生物组的研究对于监测公共卫生和基础设施的健康状况非常有用,但污水微生物组的变化方式往往存在很大的不确定性。我们对在一个污水系统中的 17 个位置采集的为期 3 周的污水样本中回收的 DNA 进行了测序,以确定这些群落如何随时间和空间变化。大多数污水细菌及其携带的抗生素耐药基因并非来自人类粪便,但人类的使用模式确实影响了我们在这些系统中发现的细菌数量和类型随时间的变化。同样,污水群落,包括细菌及其病毒,也因污水网络中的位置而异,这突出了监测和理解污水微生物组所面临的挑战和机遇。