ReviewRNA biology2017
Why so narrow: Distribution of anti-sense regulated, type I toxin-antitoxin systems compared with type II and type III systems.
Review in RNA biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
What it found
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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.
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.
Who cites it
20 citing papers in PubMed, 38 citations in OpenAlex.
- Spontaneous TisB toxin expression modulatesFEMS microbes · 2026Article
- MazF endoribonuclease promotes resolution of transcription-replication conflicts at ribosomal RNA genes in Escherichia coli.Nucleic acids research · 2025Article
- Article
- Type I toxin-antitoxin systems in bacteria: from regulation to biological functions.EcoSal Plus · 2024Review
- Relevance of charged and polar amino acids for functionality of membrane toxin TisB.Scientific reports · 2024Article
- Unraveling the evolutionary dynamics of toxin-antitoxin systems in diverse genetic lineages ofmBio · 2024Article
- A Shift in Perspective: A Role for the Type I Toxin TisB as Persistence-Stabilizing Factor.Frontiers in microbiology · 2022Article
- RNA Regulated Toxin-Antitoxin Systems in Pathogenic Bacteria.Frontiers in cellular and infection microbiology · 2021Review
- Role of VapBC12 Toxin-Antitoxin Locus in Cholesterol-Induced Mycobacterial Persistence.mSystems · 2020Article
- Type I toxin-antitoxin systems contribute to the maintenance of mobile genetic elements in Clostridioides difficile.Communications biology · 2020Article
- Article
- Article
- Type II and type IV toxin-antitoxin systems show different evolutionary patterns in the global Klebsiella pneumoniae population.Nucleic acids research · 2020Article
- The Variety in the Common Theme of Translation Inhibition by Type II Toxin-Antitoxin Systems.Frontiers in genetics · 2020Review
- Bioinformatic and mutational studies of related toxin-antitoxin pairs inThe Journal of biological chemistry · 2019Article
- Noncoding RNA.Microbiology spectrum · 2019Review
- SLING: a tool to search for linked genes in bacterial datasets.Nucleic acids research · 2018Article
- Type I Toxin-Antitoxin Systems: Regulating Toxin Expression via Shine-Dalgarno Sequence Sequestration and Small RNA Binding.Microbiology spectrum · 2018Review
- Widespread Antisense Transcription in Prokaryotes.Microbiology spectrum · 2018Review
- Discovery of new type I toxin-antitoxin systems adjacent to CRISPR arrays in Clostridium difficile.Nucleic acids research · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Toxin-antitoxin (TA) systems are gene modules that appear to be horizontally mobile across a wide range of prokaryotes. It has been proposed that type I TA systems, with an antisense RNA-antitoxin, are less mobile than other TAs that rely on direct toxin-antitoxin binding but no direct comparisons have been made. We searched for type I, II and III toxin families using iterative searches with profile hidden Markov models across phyla and replicons. The distribution of type I toxin families were comparatively narrow, but these patterns weakened with recently discovered families. We discuss how the function and phenotypes of TA systems as well as biases in our search methods may account for differences in their distribution.
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Registered trials
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 OpenQuestion graph.