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Longitudinal wastewater sampling in buildings reveals temporal dynamics of metabolites

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...

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Autores principales: Evans, Ethan D., Dai, Chengzhen, Isazadeh, Siavash, Park, Shinkyu, Ratti, Carlo, Alm, Eric J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7351223/
https://www.ncbi.nlm.nih.gov/pubmed/32598361
http://dx.doi.org/10.1371/journal.pcbi.1008001
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author Evans, Ethan D.
Dai, Chengzhen
Isazadeh, Siavash
Park, Shinkyu
Ratti, Carlo
Alm, Eric J.
author_facet Evans, Ethan D.
Dai, Chengzhen
Isazadeh, Siavash
Park, Shinkyu
Ratti, Carlo
Alm, Eric J.
author_sort Evans, Ethan D.
collection PubMed
description 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.
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spelling pubmed-73512232020-07-22 Longitudinal wastewater sampling in buildings reveals temporal dynamics of metabolites Evans, Ethan D. Dai, Chengzhen Isazadeh, Siavash Park, Shinkyu Ratti, Carlo Alm, Eric J. PLoS Comput Biol Research Article 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. Public Library of Science 2020-06-29 /pmc/articles/PMC7351223/ /pubmed/32598361 http://dx.doi.org/10.1371/journal.pcbi.1008001 Text en © 2020 Evans et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Evans, Ethan D.
Dai, Chengzhen
Isazadeh, Siavash
Park, Shinkyu
Ratti, Carlo
Alm, Eric J.
Longitudinal wastewater sampling in buildings reveals temporal dynamics of metabolites
title Longitudinal wastewater sampling in buildings reveals temporal dynamics of metabolites
title_full Longitudinal wastewater sampling in buildings reveals temporal dynamics of metabolites
title_fullStr Longitudinal wastewater sampling in buildings reveals temporal dynamics of metabolites
title_full_unstemmed Longitudinal wastewater sampling in buildings reveals temporal dynamics of metabolites
title_short Longitudinal wastewater sampling in buildings reveals temporal dynamics of metabolites
title_sort longitudinal wastewater sampling in buildings reveals temporal dynamics of metabolites
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7351223/
https://www.ncbi.nlm.nih.gov/pubmed/32598361
http://dx.doi.org/10.1371/journal.pcbi.1008001
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