Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Monitoring of functional gene responses to biostimulation from TCE-contaminated sites using a functional microarray

ABSTRACT: This SuperSeries is composed of the following subset Series: GSE28606: Monitoring of functional gene responses to ERD (enhanced reductive dechlorination) from four TCE-contaminated sites GSE28608: Monitoring of functional gene responses to biostimulation from a TCE-contaminated site Refer to individual Series

ORGANISM(S): groundwater metagenome

SUBMITTER: Peyret Pierre

PROVIDER: E-GEOD-28609 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Publications

In situ TCE degradation mediated by complex dehalorespiring communities during biostimulation processes.

Dugat-Bony Eric E Biderre-Petit Corinne C Jaziri Faouzi F David Maude M MM Denonfoux Jérémie J Lyon Delina Y DY Richard Jean-Yves JY Curvers Cyrille C Boucher Delphine D Vogel Timothy M TM Peyretaillade Eric E Peyret Pierre P

Microbial biotechnology 20120321 5

The bioremediation of chloroethene contaminants in groundwater polluted systems is still a serious environmental challenge. Many previous studies have shown that cooperation of several dechlorinators is crucial for complete dechlorination of trichloroethene to ethene. In the present study, we used an explorative functional DNA microarray (DechloArray) to examine the composition of specific functional genes in groundwater samples in which chloroethene bioremediation was enhanced by delivery of hy ...[more]

PMID: 22432919

Similar Datasets

Project description:Metagenome-assembled genomes (MAGs) have revealed the existence of novel bacterial and archaeal groups and provided insight into their genetic potential. However, metagenomics and even metatranscriptomics cannot resolve how the genetic potential translates into metabolic functions and physiological activity. Here, we present a novel approach for the quantitative and organism-specific assessment of the carbon flux through microbial communities with stable isotope probing-metaproteomics and integration of temporal dynamics in 13C incorporation by Stable Isotope Cluster Analysis (SIsCA). We used groundwater microcosms labeled with 13CO2 and D2O as model systems and stimulated them with reduced sulfur compounds to determine the ecosystem role of chemolithoautotrophic primary production. Raman microspectroscopy detected rapid deuterium incorporation in microbial cells from 12 days onwards, indicating activity of the groundwater organisms. SIsCA revealed that groundwater microorganisms fell into five distinct carbon assimilation strategies. Only one of these strategies, comprising less than 3.5% of the community, consisted of obligate autotrophs (Thiobacillus), with a 13C incorporation of approximately 95%. Instead, mixotrophic growth was the most successful strategy, and was represented by 12 of the 15 MAGs expressing pathways for autotrophic CO2 fixation, including Hydrogenophaga, Polaromonas and Dechloromonas, with varying 13C incorporation between 5% and 90%. Within 21 days, 43% of carbon in the community was replaced by 13C, increasing to 80% after 70 days. Of the 31 most abundant MAGs, 16 expressed pathways for sulfur oxidation, including strict heterotrophs. We concluded that chemolithoautotrophy drives the recycling of organic carbon and serves as a fill-up function in the groundwater. Mixotrophs preferred the uptake of organic carbon over the fixation of CO2, and heterotrophs oxidize inorganic compounds to preserve organic carbon. Our study showcases how next-generation physiology approach like SIsCA can move beyond metagenomics studies by providing information about expression of metabolic pathways and elucidating the role of MAGs in ecosystem functioning.

Dataset Information

Monitoring of functional gene responses to biostimulation from TCE-contaminated sites using a functional microarray

Publications

In situ TCE degradation mediated by complex dehalorespiring communities during biostimulation processes.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure