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A comparative genomics methodology reveals a widespread family of membrane-disrupting T6SS effectors

Author

Listed:
  • Chaya M. Fridman

    (Tel Aviv University)

  • Kinga Keppel

    (Tel Aviv University)

  • Motti Gerlic

    (Tel Aviv University)

  • Eran Bosis

    (ORT Braude College of Engineering)

  • Dor Salomon

    (Tel Aviv University)

Abstract

Gram-negative bacteria deliver effectors via the type VI secretion system (T6SS) to outcompete their rivals. Each bacterial strain carries a different arsenal of effectors; the identities of many remain unknown. Here, we present an approach to identify T6SS effectors encoded in bacterial genomes of interest, without prior knowledge of the effectors’ domain content or genetic neighborhood. Our pipeline comprises a comparative genomics analysis followed by screening using a surrogate T6SS+ strain. Using this approach, we identify an antibacterial effector belonging to the T6SS1 of Vibrio parahaemolyticus, representing a widespread family of T6SS effectors sharing a C-terminal domain that we name Tme (Type VI membrane-disrupting effector). Tme effectors function in the periplasm where they intoxicate bacteria by disrupting membrane integrity. We believe our approach can be scaled up to identify additional T6SS effectors in various bacterial genera.

Suggested Citation

  • Chaya M. Fridman & Kinga Keppel & Motti Gerlic & Eran Bosis & Dor Salomon, 2020. "A comparative genomics methodology reveals a widespread family of membrane-disrupting T6SS effectors," Nature Communications, Nature, vol. 11(1), pages 1-14, December.
    • Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-14951-4
    DOI: 10.1038/s41467-020-14951-4
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    Cited by:

    1. Katarzyna Kanarek & Chaya Mushka Fridman & Eran Bosis & Dor Salomon, 2023. "The RIX domain defines a class of polymorphic T6SS effectors and secreted adaptors," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    2. Danielle Miller & Adi Stern & David Burstein, 2022. "Deciphering microbial gene function using natural language processing," Nature Communications, Nature, vol. 13(1), pages 1-11, December.

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