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See detailRoles of bacteriophages, plasmids and CRISPR immunity in microbial community dynamics revealed using time-series integrated meta-omics
Martinez Arbas, Susana UL; Narayanasamy, Shaman; Herold, Malte et al

in Nature Microbiology (2020)

Viruses and plasmids (invasive mobile genetic elements (iMGEs)) have important roles in shaping microbial communities, but their dynamic interactions with CRISPR-based immunity remain unresolved. We ... [more ▼]

Viruses and plasmids (invasive mobile genetic elements (iMGEs)) have important roles in shaping microbial communities, but their dynamic interactions with CRISPR-based immunity remain unresolved. We analysed generation-resolved iMGE–host dynamics spanning one and a half years in a microbial consortium from a biological wastewater treatment plant using integrated meta-omics. We identified 31 bacterial metagenome-assembled genomes encoding complete CRISPR–Cas systems and their corresponding iMGEs. CRISPR-targeted plasmids outnumbered their bacteriophage counterparts by at least fivefold, highlighting the importance of CRISPR-mediated defence against plasmids. Linear modelling of our time-series data revealed that the variation in plasmid abundance over time explained more of the observed community dynamics than phages. Community-scale CRISPR-based plasmid–host and phage–host interaction networks revealed an increase in CRISPR-mediated interactions coinciding with a decrease in the dominant ‘Candidatus Microthrix parvicella’ population. Protospacers were enriched in sequences targeting genes involved in the transmission of iMGEs. Understanding the factors shaping the fitness of specific populations is necessary to devise control strategies for undesirable species and to predict or explain community-wide phenotypes. [less ▲]

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See detailUsing metabolic networks to resolve ecological properties of microbiomes
Muller, Emilie UL; Faust, Karoline; Widder, Stefanie et al

in Current Opinion in Systems Biology (2018)

The systematic collection, integration and modelling of high-throughput molecular data (multi-omics) allows the detailed characterisation of microbiomes in situ. Through metabolic trait inference ... [more ▼]

The systematic collection, integration and modelling of high-throughput molecular data (multi-omics) allows the detailed characterisation of microbiomes in situ. Through metabolic trait inference, metabolic network reconstruction and modelling, we are now able to define ecological interactions based on metabolic exchanges, identify keystone genes, functions and species, and resolve ecological niches of constituent microbial populations. The resulting knowledge provides detailed information on ecosystem functioning. However, as microbial communities are dynamic in nature the field needs to move towards the integration of time- and space-resolved multi-omic data along with detailed environmental information to fully harness the power of community- and population-level metabolic network modelling. Such approaches will be fundamental for future targeted management strategies with wide-ranging applications in biotechnology and biomedicine. [less ▲]

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