Wastewater epidemiology is a promising tool for population health monitoring, with applications ranging from infectious disease surveillance to drug consumption estimation. To date, however, there are few examples of wastewater epidemiology implemented in practice. Here, we propose and implement a novel sampling approach to produce data useful to public health monitoring. We integrate sewage network and population information to sample a manhole representative of a residential community and show that the wastewater sampled here contains more human-derived bacteria and metabolites than at downstream wastewater treatment plants, the common sampling locations in wastewater epidemiology. We applied untargeted metabolomics to identify multiple glucuronide compounds in upstream sewage. These molecules are indicative of direct human excretion and are typically degraded too quickly to be detected at wastewater treatment plants. We show that diurnal variations during 24-hour sampling can be leveraged to identify human-associated components of the sewage metabolome and microbiome. Daily dynamics of analytically-confirmed urinary and fecal metabolites reflect human behavior but differ from each other. Finally, we putatively annotate a suite of human-associated metabolites, suggesting that mining untargeted data derived from residential sewage can expand currently-used biomarkers with direct public health or policy relevance. Together, these results suggest that implementing wastewater epidemiology in urban settings could provide a new source of community-level health data that could directly impact public health practice.

24-hour multi-omics analysis of residential sewage reflects human activity and informs public health

2019 Fall National Meeting

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