Dataset Information

Systems Biology of Lipid Accumulating Organisms

ABSTRACT: Characterization of microbial communities at the genomic, transcriptomic, proteomic and metabolomic levels, with a special interest on lipid accumulating bacterial populations, which are naturally enriched in biological wastewater treatment systems and may be harnessed for the conversion of mixed lipid substrates (wastewater) into biodiesel. The project aims to elucidate the genetic blueprints and the functional relevance of specific populations within the community. It focuses on within-population genetic and functional heterogeneity, trying to understand how fine-scale variations contribute to differing lipid accumulating phenotypes. Insights from this project will contribute to the understanding the functioning of microbial ecosystems, and improve optimization and modeling strategies for current and future biological wastewater treatment processes. This project contains datasets derived from the same biological wastewater treatment plant. The data includes metagenomes, metatranscriptomes, metaproteomes and organisms isolated in pure cultures. Characterization of microbial communities at the genomic, transcriptomic, proteomic and metabolomic levels, with a special interest on lipid accumulating bacterial populations, which are naturally enriched in biological wastewater treatment systems and may be harnessed for the conversion of mixed lipid substrates (wastewater) into biodiesel. The project aims to elucidate the genetic blueprints and the functional relevance of specific populations within the community. It focuses on within-population genetic and functional heterogeneity, trying to understand how fine-scale variations contribute to differing lipid accumulating phenotypes. Insights from this project will contribute to the understanding the functioning of microbial ecosystems, and improve optimization and modeling strategies for current and future biological wastewater treatment processes. This project contains datasets derived from the same biological wastewater treatment plant. The data includes metagenomes, metatranscriptomes, metaproteomes and organisms isolated in pure cultures.

OTHER RELATED OMICS DATASETS IN: MTBLS328MTBLS2021

INSTRUMENT(S): LTQ Orbitrap Elite

ORGANISM(S): Wastewater Metagenome

SUBMITTER: Benoit Kunath

LAB HEAD: Paul Wilmes

PROVIDER: PXD013655 | Pride | 2020-08-19

REPOSITORIES: Pride

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Dataset's files

Source:

			Action	DRS
	042913-SludgeD1_1-6.raw	Raw
	042913-SludgeD1_13-18.raw	Raw
	042913-SludgeD1_19-24.raw	Raw
	042913-SludgeD1_25-30.raw	Raw
	042913-SludgeD1_31-36.raw	Raw

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Publications

Integration of time-series meta-omics data reveals how microbial ecosystems respond to disturbance.

Herold Malte M Martínez Arbas Susana S Narayanasamy Shaman S Sheik Abdul R AR Kleine-Borgmann Luise A K LAK Lebrun Laura A LA Kunath Benoît J BJ Roume Hugo H Bessarab Irina I Williams Rohan B H RBH Gillece John D JD Schupp James M JM Keim Paul S PS Jäger Christian C Hoopmann Michael R MR Moritz Robert L RL Ye Yuzhen Y Li Sujun S Tang Haixu H Heintz-Buschart Anna A May Patrick P Muller Emilie E L EEL Laczny Cedric C CC Wilmes Paul P

Nature communications 20201019 1

The development of reliable, mixed-culture biotechnological processes hinges on understanding how microbial ecosystems respond to disturbances. Here we reveal extensive phenotypic plasticity and niche complementarity in oleaginous microbial populations from a biological wastewater treatment plant. We perform meta-omics analyses (metagenomics, metatranscriptomics, metaproteomics and metabolomics) on in situ samples over 14 months at weekly intervals. Based on 1,364 de novo metagenome-assembled ge ...[more]

PMID: 33077707

Publication: 1/2

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