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

Abstract

High-throughput molecular analysis of sewage is a promising tool for precision public health. Here, we combine sewer network and demographic data to identify a residential catchment for sampling, and explore the potential of applying untargeted genomics and metabolomics to sewage to collect actionable public health data. We find that wastewater sampled upstream in a residential catchment is representative of the human microbiome and metabolome, and we are able to identify glucuronidated compounds indicative of direct human excretion, which are typically degraded too quickly to be detected at treatment plants. We show that diurnal variations during 24-hour sampling can be leveraged to discriminate between biomarkers in sewage that are associated with human activity from those related to the environmental background. Finally, we putatively annotate a suite of human-associated metabolites, including pharmaceuticals, food metabolites, and biomarkers of human health and activity, suggesting that mining untargeted data derived from residential sewage can expand currently-used biomarkers with direct public health or policy relevance. process sewage non-stop through one day, and for Herbie from Cambridge Public Works for providing his good humor and professional insights during our many sampling trips. We thank the generous sponsorship of the Kuwait Foundation for Advancement of Sciences, and the MIT Center for Microbiome Informatics and Therapeutics provided support for computational resources. We thank the WHOI FT-MS facility for sample analysis and Krista Longnecker for training in metabolomics data analysis and discussions throughout the study.

Longitudinal wastewater sampling in buildings reveals temporal dynamics of metabolites

“…GP cluster modeling displayed minimal day-to-day predictive power, and mean reversion, suggesting that high frequency (daily) sampling is important for capturing the observed unpredictable alterations. As a previous 24-hour metabolomics analysis [23] demonstrated strong…”

“…Adding this temporal component, without substantial wastewater aggregation, may benefit future wastewater metabolomics studies by revealing community-specific metabolite dynamics and the daily burden of environmental pollutants, drugs, or lifestyle-related small molecules. Longitudinal sampling uncovered highly dynamic and unique building profiles that would be lost with WWTP-based sampling [23] or by sampling over longer time periods. For instance, the observation of significantly different features on weekdays versus weekends in multipurpose building 1 are likely reflective of a five-day workweek with a lower weekend occupancy, something not observed for the residential buildings.…”

“…However, the temporal component provides an averaged signal, even with multiple single day composite samples. An alternative, the approach we take here, is to perform close-to-source, short continuous sampling (or periodic grab sampling) without combination [23]. The second route often requires multiple locations and high sampling frequency (hourly to daily or near-daily), necessitating a large number of samples.…”

Longitudinal wastewater sampling in buildings reveals temporal dynamics of metabolites

“…GP cluster modeling displayed minimal day-to-day predictive power, and rapid reversion following large deviations from the mean. As a previous 24-hour metabolomics analysis 23 demonstrated strong diurnal patterns in wastewater, we used a small length scale parameter for the GP. Using a conservative 3-hour length scale, information decayed rapidly, providing no day-to-day predictive power.…”

“…However, the temporal component provides an averaged signal, even with multiple single day composite samples. An alternative is to perform close-to-source, periodic grab sampling or short continuous sampling without combination 23 . The second route often requires multiple locations and high sampling frequency (hourly to daily or near-daily), necessitating a large number of samples.…”