Summary of Study ST001357
This data is available at the NIH Common Fund's National Metabolomics Data Repository (NMDR) website, the Metabolomics Workbench, https://www.metabolomicsworkbench.org, where it has been assigned Project ID PR000927. The data can be accessed directly via it's Project DOI: 10.21228/M8VT32 This work is supported by NIH grant, U2C- DK119886.
See: https://www.metabolomicsworkbench.org/about/howtocite.php
This study contains a large results data set and is not available in the mwTab file. It is only available for download via FTP as data file(s) here.
| Study ID | ST001357 |
| Study Title | Longitudinal wastewater sampling and untargeted metabolomics of three buildings |
| Study Summary | 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. |
| Institute | Massachusetts Institute of Technology |
| Last Name | ethan |
| First Name | evans |
| Address | 77 Massachusetts Ave, Cambridge, MA, 02139, USA |
| eevans@mit.edu | |
| Phone | 617-253-2726 |
| Submit Date | 2020-03-20 |
| Raw Data Available | Yes |
| Raw Data File Type(s) | mzML |
| Analysis Type Detail | LC-MS |
| Release Date | 2020-06-08 |
| Release Version | 1 |
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Sample Preparation:
| Sampleprep ID: | SP001439 |
| Sampleprep Summary: | The filtrate from the previous step was collected in amber glass vials, the pH was adjusted to between 2 and 3, and stored at -80 ࿁C, all in less than 2 hours post sampling. |
