Studying microbiomes by high-definition metagenomics

In silico genomics

Although microbial communities (“microbiomes”) are central to life on earth, they largely remained terra incognita until recently. By developing a quickly growing collection of tools in microbial systems biology we have just started learning about the compositions, interactions and functions of microbiomes.

The rapid improvement of DNA sequencing methods has driven the development of new methods for predictive modeling of microbiomes and for time series analysis of microbial communities, allowing the transition from description to causality and prediction. Microbial diversity is so far mostly described by metagenomic data. Consequently, most of the current work in microbiome modeling is based on it. Tractable microbial communities are studied to bridge the gap between observations of patterns of microbial diversity and mechanisms that can explain these patterns.

Compared to amplicon-based microbial diversity data, genomic and metagenomic information based on whole genome sequencing is more difficult to obtain and more costly. Therefore only few studies have used such data for developing system-scale models. It was, however, demonstrated that metabolic capabilities of microbiomes can already be approached by modeling techniques, which also provide mechanistic insights.

The ultimate goal of enhancing our toolbox of methods in microbial systems biology is to test scientific theory and address scientific questions in important areas such as medicine, microbiology, microbial ecology and biotechnology. The potential of metagenomics and metatranscriptomics in studying the ecology of microorganisms in many habitats will only be realized when genome-centric approaches are used in combination with other relevant techniques in experiments designed to test specific questions and hypotheses. To realize this concept, current proposals suggest an “International Microbiome Initiative” and a “Unified Microbiome Initiative”. These initiatives envision evidence-based, model-informed microbiome research.

At CUBE we therefore focus on the latest developments in metagenomics, the transition from “gene-centric” to “genome-centric” approaches. We apply and improve these state-of-the-art methods with our collaboration partners. We wish to better understand microbiomes of humans, plants and animals. We also study the structure and function of diverse microbial ecosystems, such as soil, marine holobionts and engineered systems.

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