Comparative integrated omics: identification of key functionalities in microbial community-wide metabolic networks

in Biofilms and Microbiomes (2015), 1(15007),

BACKGROUND: Mixed microbial communities underpin important biotechnological processes such as biological wastewater treatment (BWWT). A detailed knowledge of community structure and function relationships ... [more ▼]

BACKGROUND: Mixed microbial communities underpin important biotechnological processes such as biological wastewater treatment (BWWT). A detailed knowledge of community structure and function relationships is essential for ultimately driving these systems towards desired outcomes, e.g., the enrichment in organisms capable of accumulating valuable resources during BWWT. METHODS: A comparative integrated omic analysis including metagenomics, metatranscriptomics and metaproteomics was carried out to elucidate functional differences between seasonally distinct oleaginous mixed microbial communities (OMMCs) sampled from an anoxic BWWT tank. A computational framework for the reconstruction of community-wide metabolic networks from multi-omic data was developed. These provide an overview of the functional capabilities by incorporating gene copy, transcript and protein abundances. To identify functional genes, which have a disproportionately important role in community function, we define a high relative gene expression and a high betweenness centrality relative to node degree as gene-centric and network topological features, respectively. RESULTS: Genes exhibiting high expression relative to gene copy abundance include genes involved in glycerolipid metabolism, particularly triacylglycerol lipase, encoded by known lipid accumulating populations, e.g., Candidatus Microthrix parvicella. Genes with a high relative gene expression and topologically important positions in the network include genes involved in nitrogen metabolism and fatty acid biosynthesis, encoded by Nitrosomonas spp. and Rhodococcus spp. Such genes may be regarded as ‘keystone genes’ as they are likely to be encoded by keystone species. CONCLUSION: The linking of key functionalities to community members through integrated omics opens up exciting possibilities for devising prediction and control strategies for microbial communities in the future. [less ▲]

The sequential isolation of metabolites, RNA, DNA, and proteins from a single, undivided mixed microbial community sample

in Methods in Enzymology (2014)

Integrated omics of microbial consortia, comprising systematized metagenomic, metatranscriptomic, metaproteomic and meta-metabolomic analyses, allows in-depth characterization of organismal and functional ... [more ▼]

Integrated omics of microbial consortia, comprising systematized metagenomic, metatranscriptomic, metaproteomic and meta-metabolomic analyses, allows in-depth characterization of organismal and functional diversity in situ. To allow meaningful meta-omic data integration, truly systematic measurements of the typically heterogeneous sample biomass is required. Therefore, there is a need for analyzing biomolecular fractions obtained from single, undivided samples. Here, we share a methodological workflow for the reproducible isolation of concomitant polar and non-polar metabolites, RNA, DNA and proteins from samples obtained from a biological wastewater treatment plant. The methodological framework is applicable to other biological samples [1,2], is compatible with different kits for biomacromolecular isolation [1,2] with minimal tailoring, and represents an important first step in standardization for the emerging field of Molecular Eco-Systems Biology. [less ▲]

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

Poster (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 strategies (generalist versus specialist) 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 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 ▲]

The exogenous RNA spectrum in human plasma and the gastrointestinal tract

Poster (2013, October)

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 ▲]

Eco-systems biology of microbial communities: integration of biomolecular information from unique samples

Poster (2013)

In microbial ecology, high-resolution molecular approaches are essential to characterize the vast organismal and functional diversity and to understand the interactions between environmental factors and ... [more ▼]

In microbial ecology, high-resolution molecular approaches are essential to characterize the vast organismal and functional diversity and to understand the interactions between environmental factors and microbial communities (MCs). Molecular eco-systems biology based on the integration of genomics and functional omics, allows conclusive links to be drawn between genetic potential and function. However, the field faced major challenges arising from the heterogeneity and dynamics of MCs. Hence, to facilitate meaningful data integration, analysis and modeling, it is crucial to obtain standardised, reproducible and simultaneous measurements of multiple features from a unique sample. We have developed a new methodological framework for the isolation of high-quality DNA, large and small RNA, proteins and metabolites fractions from undivided MC samples. The methodology is based on cryogenic sample preservation and cell lysis. Metabolites are first extracted using organic solvents, followed by sequential isolation of biomacromolecules using chromatographic spin column technology. The methodology was validated by comparison to commonly used dedicated methods and its broad applicability was demonstrated on MCs of biotechnological, environmental and medical interest. Applying this method to sewage plant MCs has allowed us to determine community-level keystone genes and to probe the functional relevance of the population-level composite genomes, leading to the identification of key players of the community. This methodological framework lays the foundation for standardized molecular eco-systems biology and offers exciting prospects for elucidating the genetic blueprints and the functional relevance of specific populations within MCs, particularly in relation to environment-driven demography changes leading to catastrophic bifurcations. [less ▲]

A biomolecular isolation framework for eco-systems biology

in ISME Journal (2013), 7(1), 110-121

Mixed microbial communities are complex, dynamic and heterogeneous. It is therefore essential that biomolecular fractions obtained for high-throughput omic analyses are representative of single samples to ... [more ▼]

Mixed microbial communities are complex, dynamic and heterogeneous. It is therefore essential that biomolecular fractions obtained for high-throughput omic analyses are representative of single samples to facilitate meaningful data integration, analysis and modeling. We have developed a new methodological framework for the reproducible isolation of high-quality genomic DNA, large and small RNA, proteins, and polar and non-polar metabolites from single unique mixed microbial community samples. The methodology is based around reproducible cryogenic sample preservation and cell lysis. Metabolites are extracted first using organic solvents, followed by the sequential isolation of nucleic acids and proteins using chromatographic spin columns. The methodology was validated by comparison to traditional dedicated and simultaneous biomolecular isolation methods. To prove the broad applicability of the methodology, we applied it to microbial consortia of biotechnological, environmental and biomedical research interest. The developed methodological framework lays the foundation for standardized molecular eco-systematic studies on a range of different microbial communities in the future. [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 ▲]

A biomolecular isolation framework for eco-systems biology

Poster (2012)

A Biomolecular Isolation Framework for Molecular Eco-Systems Biology

Poster (2012)

With the advent of high-throughput omic technologies, powerful and sensitive methods are available for the analysis of nucleic acid, protein and small molecule complements obtained from biological samples ... [more ▼]

With the advent of high-throughput omic technologies, powerful and sensitive methods are available for the analysis of nucleic acid, protein and small molecule complements obtained from biological samples. Molecular eco-systems biology studies based on the integration of genomic, transcriptomic, proteomic and metabolomic data are faced with major challenges arising from the complexity, dynamics and heterogeneity of mixed microbial consortia. In order to facilitate meaningful data integration, analysis and modeling, it is essential that biomolecular fractions obtained for high-throughput omic analyses are representative of single unique samples. We have developed a new methodological framework for the reproducible isolation of high-quality genomic DNA, large and small RNA, proteins, and polar and non-polar metabolites from single unique mixed microbial community samples. The methodology is based around reproducible cryogenic sample preservation and cell lysis. Metabolites are extracted first using organic solvents, followed by the sequential isolation of nucleic acids and proteins using chromatographic spin column technology. The methodology was validated by comparison to traditional dedicated and simultaneous biomolecular isolation methods. To prove the broad applicability of the methodology, we applied it to microbial consortia of biotechnological, environmental and medical interest. Importantly, the developed methodology will allow exploitation of the inherent heterogeneity and dynamics within microbial consortia through spatial and temporal sampling of biological systems to allow later deconvolution of community-wide, population-wide and individual-level processes using the generated omic data. This approach has the potential to identify associations between distinct biomolecules and which may provide pointers towards unravelling previously unknown metabolic processes. Finally, by providing a standardized workflow, the methodology lays the foundation for comparative eco-systematic studies of different natural microbial consortia in the future. [less ▲]