Evidence map›Paper›PMID 39404847›Full record

ArticleMolecular biology and evolution2024

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

Jonathan H Bethke, Jeffrey Kimbrel, Yongqin Jiao, Dante Ricci

Abstract read
In one paragraph

Article in Molecular biology and evolution, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Development of a Potent and FunctionalJournal of medicinal chemistry · 2025
    Article
  6. Article
  7. Review
  8. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Jonathan H BethkeBiosciences and Biotechnology Division, Physical and Life Science Directorate, Lawrence Livermore National Laboratory, Livermore, CA 94550, USA.ORCID 0000-0002-9900-2369
Jeffrey KimbrelBiosciences and Biotechnology Division, Physical and Life Science Directorate, Lawrence Livermore National Laboratory, Livermore, CA 94550, USA.ORCID 0000-0001-7213-9392
Yongqin JiaoBiosciences and Biotechnology Division, Physical and Life Science Directorate, Lawrence Livermore National Laboratory, Livermore, CA 94550, USA.ORCID 0000-0002-6798-5823
Dante RicciBiosciences and Biotechnology Division, Physical and Life Science Directorate, Lawrence Livermore National Laboratory, Livermore, CA 94550, USA.ORCID 0000-0003-4448-6076

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Gene Transfer, HorizontalPlasmidsToxin-Antitoxin SystemsBacteriacommunityhorizontal gene transfernetworkplasmidtoxin–antitoxin system

Identifiers

PMID39404847
PMCPMC11523183

What Socratic holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.