Longitudinal wastewater sampling in buildings reveals temporal dynamics of metabolites

Ethan D. Evans, Chengzhen Dai, Siavash Isazadeh, Shinkyu Park, Carlo Ratti, Eric J. Alm

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


Direct sampling of building wastewater has the potential to enable “precision public health” observations and interventions. Temporal sampling offers additional dynamic information that can be used to increase the informational content of individual metabolic “features”, but few studies have focused on high-resolution sampling. Here, we sampled three spatially close buildings, revealing individual metabolomics features, retention time (rt) and mass-to-charge ratio (mz) pairs, that often possess similar stationary statistical properties, as expected from aggregate sampling. However, the temporal profiles of features-providing orthogonal information to physicochemical properties-illustrate that many possess different feature temporal dynamics (fTDs) across buildings, with large and unpredictable single day deviations from the mean. Internal to a building, numerous and seemingly unrelated features, with mz and rt differences up to hundreds of Daltons and seconds, display highly correlated fTDs, suggesting non-obvious feature relationships. Data-driven building classification achieves high sensitivity and specificity, and extracts building-identifying features found to possess unique dynamics. Analysis of fTDs from many short-duration samples allows for tailored community monitoring with applicability in public health studies.
Original languageEnglish (US)
JournalPLoS Computational Biology
Issue number6
StatePublished - Jun 1 2020
Externally publishedYes

Bibliographical note

Generated from Scopus record by KAUST IRTS on 2022-09-13

ASJC Scopus subject areas

  • Ecology
  • Cellular and Molecular Neuroscience
  • Ecology, Evolution, Behavior and Systematics
  • Genetics
  • Modeling and Simulation
  • Computational Theory and Mathematics
  • Molecular Biology


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