Community-integrated omics links dominance of a microbial generalist to fine-tuned resource usage

in Nature Communications (2014)

Microbial communities are complex and dynamic systems that are primarily structured according to their members’ ecological niches. To investigate how niche breadth (generalist versus specialist lifestyle ... [more ▼]

Microbial communities are complex and dynamic systems that are primarily structured according to their members’ ecological niches. To investigate how niche breadth (generalist versus specialist lifestyle strategies) relates to ecological success, we develop and apply an integrative workflow for the multi-omic analysis of oleaginous mixed microbial communities from a biological wastewater treatment plant. Time- and space-resolved coupled metabolomic and taxonomic analyses demonstrate that the community-wide lipid accumulation phenotype is associated with the dominance of the generalist bacterium Candidatus Microthrix spp. By integrating population-level genomic reconstructions (reflecting fundamental niches) with transcriptomic and proteomic data (realised niches), we identify finely tuned gene expression governing resource usage by Candidatus Microthrix parvicella over time. Moreover, our results indicate that the fluctuating environmental conditions constrain the accumulation of genetic variation in Candidatus Microthrix parvicella likely due to fitness trade-offs. Based on our observations, niche breadth has to be considered as an important factor for understanding the evolutionary processes governing (microbial) population sizes and structures in situ. [less ▲]

Community integrated omics links the dominance of a microbial generalist to fine-tuned resource usage

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 ▲]

Linking mixed microbial community phenotype to individual genotypes

Poster (2013)

Biological wastewater treatment is arguably the most widely used biotechnological process on Earth. Wastewater also represents a valuable energy commodity that is currently not being harnessed ... [more ▼]

Biological wastewater treatment is arguably the most widely used biotechnological process on Earth. Wastewater also represents a valuable energy commodity that is currently not being harnessed comprehensively. Mixed microbial communities that naturally occur at the air-water interface of certain biological wastewater treatment systems accumulate excess long chain fatty acids intracellularly. This phenotypic trait may potentially be exploited for the transformation of lipid-rich wastewater into biodiesel (fatty acid methyl esters). Using a molecular Eco-Systems Biology approach, we are studying which genes contribute to the lipid accumulation phenotype and, thus, overall community function. We first compared the lipid accumulation phenotype to the structure of lipid accumulating communities from a local wastewater treatment plant by coupled deep sequencing of the 16S rRNA locus, metagenome sequencing and metabolomic analysis of 4 biological replicates sampled at 4 different time points. Based on the results of these analyses and in order to obtain a detailed view of the structure and function of the respective microbial communities, metagenomic, metatranscriptomic, metaproteomic and (meta-)metabolomic analyses were completed for a single representative biological sample of highest interest. In order to facilitate meaningful data integration of this highly heterogeneous consortium, biomolecular fractions used for the omic analyses were extracted from a unique single sample using a recently developed biomolecular isolation protocol. The coupled survey and the comparative metagenomic analysis demonstrate that the communities change significantly from dates with warm water temperatures to cold water temperatures while alpha diversity remains stable. In the winter period, this switch results in a strong enrichment of a bacterial genus well known to accumulate intracellular lipids, namely Microthrix spp., a representative genome of which has recently been sequenced by us. Correlation networks based on microorganism and concomitant intra- and extra-cellular metabolite abundances provides an overview of organisms potentially involved in the community-wide lipid accumulating phenotype. A sample with the highest abundance of Microthrix spp. was subsequently chosen for the construction of a community-wide metabolic model using metagenomic, metatranscriptomic, metaproteomic and (meta-)metabolomics data. Based on these omic datasets, expressed enzyme variants linked to the lipid accumulation phenotype have been identified and are currently undergoing in vitro characterization. Meta-omic analyses offer exciting prospects for elucidating the genetic blueprints and the functional relevance of specific populations within microbial communities. Consequently, connecting the overall community phenotype to specific genotypes will allow much needed fundamental ecological understanding of microbial community and population dynamics, particularly in relation to environment-driven demography changes leading to tipping points and catastrophic bifurcations. [less ▲]

A model microbial community for Eco-Systems Biology

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 ▲]