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See detailCommunity integrated omics links the dominance of a microbial generalist to fine-tuned resource usage
Muller, Emilie UL; Pinel, Nicolás; Laczny, Cedric Christian UL et al

Scientific Conference (2014)

Microbial communities are complex and dynamic systems that are influenced by stochastic-neutral processes but are mainly structured by resource availability and usage. High-resolution “meta-omics” offer ... [more ▼]

Microbial communities are complex and dynamic systems that are influenced by stochastic-neutral processes but are mainly structured by resource availability and usage. High-resolution “meta-omics” offer exciting prospects to investigate microbial populations in their native environment. In particular, integrated meta-omics, by allowing simultaneous resolution of fundamental niches (genomics) and realised niches (transcriptomics, proteomics and metabolomics), can resolve microbial lifestyles (generalist versus specialist lifestyle strategies) in situ. We have recently developed the necessary wet- and dry-lab methodologies to carry out systematic molecular measurements of microbial consortia over space and time, and to integrate and analyse the resulting data at the population-level. We applied these methods to oleaginous mixed microbial communities located on the surface of anoxic biological wastewater treatment tanks to investigate how niche breadth (generalist versus specialist lifestyle strategies) relates to community-level phenotypes and ecological success (i.e. population size). Coupled metabolomics and 16S rRNA gene-based deep sequencing demonstrate that the community-wide lipid accumulation phenotype is associated with the dominance of Candidatus Microthrix parvicella. By integrating population-level genomic reconstructions with transcriptomic and proteomic data, we found that the dominance of this microbial generalist population results from finely tuned resource usage and optimal foraging behaviour. Moreover, the fluctuating environmental conditions constrain the accumulation of variations, leading to a genetically homogeneous population likely due to fitness trade-offs. By integrating metagenomic, metatranscriptomic, metaproteomic and metabolomic information, we demonstrate that natural microbial population sizes and structures are intricately linked to resource usage and that differing microbial lifestyle strategies may explain the varying degrees of within-population genetic heterogeneity observed in metagenomic datasets. Elucidating the exact mechanism driving fitness trade-offs, e.g., antagonistic pleiotropy or others, will require additional integrated omic datasets to be generated from samples taken over space and time. Based on our observations, niche breadth and lifestyle strategies (generalists versus specialists) have to be considered as important factors for understanding the evolutionary processes governing microbial population sizes and structures in situ. [less ▲]

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See detailTowards the Identification of Condition-Specific Microbial Populations from Human Metagenomic Data
Laczny, Cedric Christian UL; Wilmes, Paul UL

in Keller, Andreas; Meese, Eckart (Eds.) Nucleic Acids as Molecular Diagnostics (2014)

Detailed reference viewed: 129 (7 UL)
See detailA model microbial community for Eco-Systems Biology
Muller, Emilie UL; Roume, Hugo UL; Buschart, Anna UL et al

Poster (2013)

Objective Microbial communities (MCs) play crucial roles in human health and disease. In-depth characterization of the vast organismal and functional diversity of MCs is now facilitated by high-resolution ... [more ▼]

Objective Microbial communities (MCs) play crucial roles in human health and disease. In-depth characterization of the vast organismal and functional diversity of MCs is now facilitated by high-resolution molecular approaches. Systematic measurements are key for meaningful data integration, analysis and modeling. Based on a model MC from a biological wastewater treatment plant, we have developed a new framework based on wet- and dry-lab methods for the integrated analyses of MCs at the population- as well as at the community-level. Methods The overall methodological framework first relies on a standardised wet-lab procedure for the isolation of concomitant biomolecules, i.e., DNA, RNA, proteins and metabolites, from single undivided samples. Purified biomolecular fractions then are subjected to high-resolution omic analyses including metagenomics, metatranscriptomics, metaproteomics and (meta-) metabolomics. The resulting data form the input for integrated bioinformatic analyses. Population-level integrated omic analyses rely on a newly developed binning and re-assembly method, which yields near-complete genome reconstructions for dominant populations. Community-level analyses involve the reconstruction of community-wide metabolic networks. Functional omic data is then mapped onto these reconstructions and contextualized. Results Application of the population-centric workflow has allowed us to reconstruct and identify 10 major populations within the model MC and has led to the identification of a key generalist population, Candidatus Microthrix spp., within the community. Analysis of the community-wide metabolic networks has allowed the identification of keystone genes involved in lipid and nitrogen metabolism within the MC. Conclusions Our new methodological framework offers exciting new prospects for elucidating the functional relevance of specific populations and genes within MCs. The established workflows are now being applied to samples of biomedical research interest such as human gastrointestinal tract-derived samples. [less ▲]

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