Dataset Information

Longitudinal wastewater sampling and untargeted metabolomics of three buildings

ABSTRACT: 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.

ORGANISM(S): Wastewater -

TISSUE(S): Wastewater

SUBMITTER: evans ethan

PROVIDER: ST001357 | MetabolomicsWorkbench | Fri Mar 20 00:00:00 GMT 2020

REPOSITORIES: MetabolomicsWorkbench

ACCESS DATA

Dataset's files

Source:

			Action	DRS
	mwtab	Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:Oscillatory phenomena are ubiquitous across different biological scales, from individual cells to tissues and whole organisms. In physical systems, oscillatory behaviour can emerge from weak coupling of independent stochastic elements. Once established, oscillations can drive coordinated group behaviour and encode robust information through oscillation frequency or amplitude. Here we use experimentation and modelling to understand the emergence and information coding properties of oscillatory cyclic adenosine monophosphate (cAMP) signaling in D. discoideum. Oscillatory cAMP signaling drives aggregation of individual amoebae and coordinated temporal shifts in gene expression. However, it is unknown how the collective behaviour emerges and attenuates in an auto-regulatory manner where temporal transcriptional regulation must decode variation in cAMP pulse count, frequency, or amplitude. To address these questions, we identified a transcription factor, Hbx5, that is essential for the initiation of collective behaviour and its activity provides a single-cell readout of the earliest sign of cAMP signaling. This reveals stochastic pulses in cAMP signaling precede collective oscillations, with Hbx5 dependent transcriptional feedback enhancing signal sensitivity necessary for the emergence of collective oscillations. We demonstrate that once collective oscillations have been established, another cAMP-regulated transcription factor, GtaC, required for subsequent developmental progression becomes activated. Modelling and experimentation suggest that temporal differences in transcription factor activation arise from differences in the threshold at which the protein kinase, ErkB, influences their activity. This leads us to propose that changes in the amplitude of cAMP oscillations during development encode temporal information, driving the orderly progression of development. These studies thus provide crucial insights into the principles driving collective behaviour and the evolution of multicellular systems.

Dataset Information

Longitudinal wastewater sampling and untargeted metabolomics of three buildings

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets