Longitudinal wastewater sampling in buildings reveals temporal dynamics of metabolites

摘要

Understanding a community's wastewater profile may allow for specific and targeted interventions. Untargeted wastewater metabolomics provides a rich data source, but one that is high dimensional, noisy and difficult to understand. We analyze building-to-building differences and through-time patterns from temporal wastewater metabolomics data, obtained directly from three buildings. We develop and apply computational techniques to extract building-specific temporal and stationary properties for each small molecule feature. Stationary properties are predominantly conserved, but by studying the temporal dynamics, we find distinct, building-specific signatures and metabolite patterns. Interestingly, using clustering techniques and temporal similarity metrics, we find that for each building there exist groups of small molecules that possess highly similar temporal dynamics, despite having vastly different molecular properties (e.g. molecular weight or chromatographic retention time). These findings may suggest similar generative processes for such small molecules, which may lead to increased biological understanding. Additionally, our computational methods link putatively identified small molecules with unknown features. This produces a list of unknown compounds, with community-specific temporal dynamics for follow up experimental analysis and targeted discovery to better understand a community of interest.