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Metagenomic strain-resolved DNA modification patterns link extrachromosomal genetic elements to host strains.

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    We developed MODIFI, a new software tool to detect DNA modifications in metagenomes. This enables linking microbial hosts to their extrachromosomal genetic elements (ECEs) at a large scale.

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    Area of Science:

    • Microbial epigenomics
    • Metagenomics
    • Bioinformatics

    Background:

    • DNA modification is crucial for microbial defense against extrachromosomal genetic elements (ECEs).
    • ECEs typically mimic their host's DNA modification patterns.
    • Existing tools for DNA modification detection are ineffective for metagenomic analysis.

    Purpose of the Study:

    • To introduce MODIFI, a novel software for detecting DNA modifications within metagenomes.
    • To enable the linkage of ECEs to their microbial hosts using metagenomic data.
    • To overcome the limitations of current tools in analyzing microbial epigenomics at scale.

    Main Methods:

    • MODIFI utilizes PacBio HiFi reads to calculate background signal levels for k-mers, assuming most are unmodified.
    • This approach eliminates the necessity for matched control experiments.
    • The software was validated using over 1,000 isolate and mock microbiome datasets.

    Main Results:

    • MODIFI successfully identified 315 strain-resolved, non-redundant ECE-host linkages in diverse metagenomes.
    • The study demonstrated simultaneous alterations in host and plasmid methylation motifs in Enterococcus faecalis within infant gut microbiomes.
    • The software proves effective in linking ECEs to their hosts in complex microbial communities.

    Conclusions:

    • MODIFI addresses a significant challenge in DNA modification analysis, particularly in metagenomic contexts.
    • This tool provides a foundational capability for advancing the field of microbial epigenomics.
    • MODIFI facilitates a deeper understanding of host-ECE interactions and microbial community dynamics.