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Mobile genetic elements are active and responsive to community context in model microbial consortium

Insertion and excision of genomic islands (GIs), chromosomally-integrated mobile genetic elements (MGEs), are major sources of microbial genome plasticity and can impact gene expression and phenotype of the host organism. GI mobilization also influences microbial communities beyond the host organism as GI excision generates MGEs that can be transferred between community members through horizontal…

Mobile genetic elements (MGEs), such as genomic islands (GIs), are capable of insertion and excision within microbial genomes, leading to significant changes in gene expression and host phenotype. These GIs can also affect entire microbial communities beyond the host organism, as their excision can generate new MGEs that spread through horizontal gene transfer, or induce prophages that may kill host populations, thereby altering community structure.

Recent computational methods now allow for precise mapping of GIs in genomes and sensitive detection of GI excision from deep-genome sequencing data. Researchers applied these techniques to metagenomic datasets from a defined soil microbial consortium grown on glass beads under hydration stress, and compared the results with those observed in monoculture.

The findings revealed that under the more environmentally structured conditions of the community growth, GI excision was more abundant and involved a wider range of host species and GI types compared to isolate growth conditions. By combining metatranscriptomic and metaproteomic data, the researchers identified patterns of GI gene expression associated with induction.

Specifically, three GIs demonstrated particularly high excision rates alongside strong transcription, numerous detected proteins, and evidence of association with potential transfer particles, such as phages or vesicles. These results suggest that studies focusing on single isolates may overlook a significant portion of environment-responsive GI activity.

Overall, this work establishes a framework for analyzing multi-omic datasets to quantify dynamic genome restructuring, identify active but understudied GIs, and generate hypotheses about the processes that drive microbial genome plasticity and gene flow.

Written by urgent.news from bioRxiv's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.

Read the original at biorxiv.org →

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