Proteomics

Dataset Information

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Integrated meta-omic analysis of a lignocellulose-degrading microbial community


ABSTRACT: Microbial communities that degrade lignocellulosic biomass are typified by high levels of species- and strain-level complexity, as well as synergistic interactions between both cellulolytic and non-cellulolytic microorganisms. Here we deconvoluted a highly efficient cellulose-degrading and methanogenic consortium (SEM1b) that is co-dominated by Clostridium (Ruminiclostridium) thermocellum and multiple heterogenic strains affiliated to C. proteolyticus. A time-series analysis was performed over the entire lifetime span of the microbial community and comprised of metagenomic, metatranscriptomic, metabolomics, metaproteomic and 16S rRNA gene analysis for 8 time points, in triplicate. Metagenomic analysis of SEM1b recovered metagenome-assembled genomes (MAGs) for each constituent population, whereas in parallel two novel strains of C. proteolyticus were isolated and sequenced. Both the recovered MAGs and the isolated strains were used as a database for further functional meta-omics. Absolute quantitative metatranscriptomics was performed thanks the spike-in of an in vitro transcribed RNA as an internal standard and label-free quantification was used for the metaproteomic analysis. The present dataset has been used for several publications. The first aim of the project was to characterize the interactions between uncultured populations in a lignocellulose-degrading community. Furthermore, because of the in-depth multi-omics characterization of the community, the dataset was used to develop new approaches for meta-omics integration as well as to assess the protein-to-RNA ratio of multiple microbial populations simultaneously. Modifications of multi-omics toolkits allowed us to assess the linearity between transcriptome and proteome for each population over time and reveal deeper functional-related trends and integrative co-dependent metabolisms that drive the overall phenotype of microbial communities.

INSTRUMENT(S): Q Exactive

ORGANISM(S): [clostridium] Stercorarium Acetomicrobium Mobile Ruminiclostridium Thermocellum Coprothermobacter Proteolyticus Tepidanaerobacter Acetatoxydans Methanothermobacter Thermautotrophicus Tepidimicrobium Xylanilyticum

SUBMITTER: Magnus Arntzen  

LAB HEAD: Phil Pope

PROVIDER: PXD016242 | Pride | 2020-08-21

REPOSITORIES: Pride

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Publications

Integration of absolute multi-omics reveals dynamic protein-to-RNA ratios and metabolic interplay within mixed-domain microbiomes.

Delogu F F   Kunath B J BJ   Evans P N PN   Arntzen M Ø MØ   Hvidsten T R TR   Pope P B PB  

Nature communications 20200918 1


While the field of microbiology has adapted to the study of complex microbiomes via modern meta-omics techniques, we have not updated our basic knowledge regarding the quantitative levels of DNA, RNA and protein molecules within a microbial cell, which ultimately control cellular function. Here we report the temporal measurements of absolute RNA and protein levels per gene within a mixed bacterial-archaeal consortium. Our analysis of this data reveals an absolute protein-to-RNA ratio of 10<sup>2  ...[more]

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