Dissemin is shutting down on January 1st, 2025

Published in

Nature Research, Nature Microbiology, 1(6), p. 123-135, 2020

DOI: 10.1038/s41564-020-00794-8

Links

Tools

Export citation

Search in Google Scholar

Roles of bacteriophages, plasmids and CRISPR immunity in microbial community dynamics revealed using time-series integrated meta-omics

This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

Full text: Unavailable

Green circle
Preprint: archiving allowed
Orange circle
Postprint: archiving restricted
Red circle
Published version: archiving forbidden
Data provided by SHERPA/RoMEO

Abstract

AbstractViruses 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.