Evidence map›Paper›PMID 32873609›Full record

ArticlemSystems2020

RRE-Finder: a Genome-Mining Tool for Class-Independent RiPP Discovery.

Alexander M Kloosterman, Kyle E Shelton, Gilles P van Wezel, Marnix H Medema, Douglas A Mitchell

Abstract read
In one paragraph

Article in mSystems, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 78 papers.

0numbers the graph read from it
0cells of the map it votes in
78citing 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

78 citing papers in PubMed.

  1. Review
  2. Tangled Tail of Mechanically Interlocked Peptides.Journal of the American Chemical Society · 2026
    Review
  3. Article
  4. Article
  5. Article
  6. Myxarylin: TotalJournal of the American Chemical Society · 2026
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. ThiF-Like Enzyme Chemistry in Primary and Secondary Metabolism.Chembiochem : a European journal of chemical biology · 2025
    Review
  13. Article
  14. Review
  15. Article
  16. Indolylamide Macrocyclization by aOrganic letters · 2025
    Article
  17. Evolution-Guided Discovery of Antimycobacterial Triculamin-Like Lasso Peptides.Angewandte Chemie (International ed. in English) · 2025
    Article
  18. Article
  19. Biosynthesis of Macrocyclic Peptides by Formation and Crosslinking ofbioRxiv : the preprint server for biology · 2025
    Article
  20. Substrate recognition by a peptide-aminoacyl-tRNA ligase.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article

18 more citing papers are in PubMed but not listed here.

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

5 authors.

Alexander M Kloosterman *Department of Molecular Biotechnology, Institute of Biology, Leiden University, Leiden, The Netherlands.
Kyle E Shelton *Department of Chemistry, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.
Gilles P van WezelDepartment of Molecular Biotechnology, Institute of Biology, Leiden University, Leiden, The Netherlands g.wezel@biology.leidenuniv.nl marnix.medema@wur.nl douglasm@illinois.edu.ORCID https://orcid.org/0000-0003-0341-1561
Marnix H MedemaBioinformatics Group, Wageningen University, Wageningen, The Netherlands g.wezel@biology.leidenuniv.nl marnix.medema@wur.nl douglasm@illinois.edu.ORCID https://orcid.org/0000-0002-2191-2821
Douglas A MitchellDepartment of Chemistry, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA g.wezel@biology.leidenuniv.nl marnix.medema@wur.nl douglasm@illinois.edu.ORCID https://orcid.org/0000-0002-9564-0953

Funding

A Scalable Platform to Discover Antimicrobials of Ribosomal OriginR01AI144967 · NIAID · UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN · PI Douglas Alan Mitchell, WILFRED A. VAN DER DONK · 2019 to 2026
$6.0M
Training Program in Chemistry-Interface with BiologyT32GM070421 · NIGMS · UNIVERSITY OF ILLINOIS URBANA-CHAMPAIGN · PI HERGENROTHER, PAUL · 2005 to 2019
$5.4M
NIAID NIH HHS R01 AI144967NIGMS NIH HHS T32 GM070421
6 · The paper itself

Abstract

Many ribosomally synthesized and posttranslationally modified peptide classes (RiPPs) are reliant on a domain called the RiPP recognition element (RRE). The RRE binds specifically to a precursor peptide and directs the posttranslational modification enzymes to their substrates. Given its prevalence across various types of RiPP biosynthetic gene clusters (BGCs), the RRE could theoretically be used as a bioinformatic handle to identify novel classes of RiPPs. In addition, due to the high affinity and specificity of most RRE-precursor peptide complexes, a thorough understanding of the RRE domain could be exploited for biotechnological applications. However, sequence divergence of RREs across RiPP classes has precluded automated identification based solely on sequence similarity. Here, we introduce RRE-Finder, a new tool for identifying RRE domains with high sensitivity. RRE-Finder can be used in precision mode to confidently identify RREs in a class-specific manner or in exploratory mode to assist in the discovery of novel RiPP classes. RRE-Finder operating in precision mode on the UniProtKB protein database retrieved ∼25,000 high-confidence RREs spanning all characterized RRE-dependent RiPP classes, as well as several yet-uncharacterized RiPP classes that require future experimental confirmation. Finally, RRE-Finder was used in precision mode to explore a possible evolutionary origin of the RRE domain. The results suggest RREs originated from a co-opted DNA-binding transcriptional regulator domain. Altogether, RRE-Finder provides a powerful new method to probe RiPP biosynthetic diversity and delivers a rich data set of RRE sequences that will provide a foundation for deeper biochemical studies into this intriguing and versatile protein domain.

Indexed as

bioinformaticsgenome miningnatural productsRiPPsRREsecondary metabolismWeb tool

Identifiers

PMID32873609
PMCPMC7470986

What OpenQuestion holds

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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 OpenQuestion graph.