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Landscape of retron diversity across the SPIRE microbial metagenome resource reveals candidate novel type XI-like lineages

Sep 2026 · mSystems · 0 citations · 36 references
Medicine

TL;DR

This work surveyed retron RTs across the SPIRE representative metagenome collection, a non-redundant, species-level data set spanning diverse microbial habitats, and identified type XI-like retrons as a dynamic and previously underexplored evolutionary group.

Abstract

ABSTRACT Retrons are bacterial genetic elements encoding a specialized reverse transcriptase (RT) that synthesizes multicopy single-stranded DNA and are increasingly recognized as components of bacterial anti-phage defense systems. However, their diversity and ecological distribution across large-scale genomic resources remain poorly characterized. Here, we surveyed retron RTs across the SPIRE representative metagenome collection, a non-redundant, species-level data set spanning diverse microbial habitats. Using a curated panel of type-specific hidden Markov models, we identified retrons representing all canonical types together with additional divergent lineages. Retron distribution showed strong taxonomic and ecological structuring, with some groups restricted to specific bacterial phyla, whereas others were broadly distributed across environmental categories. Systematic novelty assessment identified two candidate type XI-like lineages, TXI_C2like and TXI_noncan_h, characterized by protease-independent architectures and distinct accessory modules associated with WYL- and DnaB_C-containing proteins, respectively. De novo covariance-based analyses further identified candidate msr/msd-like non-coding RNA structures in both lineages, supporting conservation of the canonical RT–ncRNA organizational framework despite extensive sequence divergence. Together, these findings expand the known diversity of retron systems and identify type XI-like retrons as a dynamic and previously underexplored evolutionary group. IMPORTANCE Retrons are bacterial genetic elements that are increasingly exploited as programmable tools for genome editing, molecular recording, and biosensing in addition to their natural role in anti-phage defense. Despite this growing biotechnological interest, the true diversity of retrons across the bacterial world has remained largely unmapped. By mining a resource of over 100,000 processed microbial metagenomes, we uncovered thousands of retron sequences spanning known types as well as previously unrecognized lineages and found that their distribution is strongly shaped by both bacterial taxonomy and ecological niche. Among these, we identified two candidate new lineages related to type XI retrons that lack the protease domain typical of this group but instead carry distinct accessory proteins, expanding the known architectural diversity of these systems. These findings broaden the catalog of retron diversity available for functional characterization and biotechnological engineering and provide a framework for prioritizing candidate lineages for future experimental validation. Retrons are bacterial genetic elements that are increasingly exploited as programmable tools for genome editing, molecular recording, and biosensing in addition to their natural role in anti-phage defense. Despite this growing biotechnological interest, the true diversity of retrons across the bacterial world has remained largely unmapped. By mining a resource of over 100,000 processed microbial metagenomes, we uncovered thousands of retron sequences spanning known types as well as previously unrecognized lineages and found that their distribution is strongly shaped by both bacterial taxonomy and ecological niche. Among these, we identified two candidate new lineages related to type XI retrons that lack the protease domain typical of this group but instead carry distinct accessory proteins, expanding the known architectural diversity of these systems. These findings broaden the catalog of retron diversity available for functional characterization and biotechnological engineering and provide a framework for prioritizing candidate lineages for future experimental validation.

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