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Toxin-Antitoxin Systems Reflect Community Interactions Through Horizontal Gene Transfer. | LitMetric

Toxin-Antitoxin Systems Reflect Community Interactions Through Horizontal Gene Transfer.

Mol Biol Evol

Biosciences and Biotechnology Division, Physical and Life Science Directorate, Lawrence Livermore National Laboratory, Livermore, CA 94550, USA.

Published: October 2024

AI Article Synopsis

  • Bacterial evolution is heavily influenced by horizontal gene transfer (HGT), which helps map community interactions but doesn't facilitate control over these interactions for engineered strains.
  • Toxin-antitoxin (TA) systems are common agents of selection in bacteria, yet their effectiveness is hindered by inconsistent distribution among host bacteria.
  • The study identifies unique TA signatures within HGT communities, linked to plasmid competition, and proposes that these signatures can aid in understanding and manipulating the interactions between plasmids, hosts, and phage within bacterial communities.

Article Abstract

Bacterial evolution through horizontal gene transfer (HGT) reflects their community interactions. In this way, HGT networks do well at mapping community interactions, but offer little toward controlling them-an important step in the translation of synthetic strains into natural contexts. Toxin-antitoxin (TA) systems serve as ubiquitous and diverse agents of selection; however, their utility is limited by their erratic distribution in hosts. Here we examine the heterogeneous distribution of TAs as a consequence of their mobility. By systematically mapping TA systems across a 10,000 plasmid network, we find HGT communities have unique and predictable TA signatures. We propose these TA signatures arise from plasmid competition and have further potential to signal the degree to which plasmids, hosts, and phage interact. To emphasize these relationships, we construct an HGT network based solely on TA similarity, framing specific selection markers in the broader context of bacterial communities. This work both clarifies the evolution of TA systems and unlocks a common framework for manipulating community interactions through TA compatibility.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11523183PMC
http://dx.doi.org/10.1093/molbev/msae206DOI Listing

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