Evidence map›Paper›PMID 30770830›Full record

ArticleNature communications2019

Structural insights into chaperone addiction of toxin-antitoxin systems.

Valérie Guillet, Patricia Bordes, Cécile Bon, Julien Marcoux, Virginie Gervais, Ambre Julie Sala, Suzana Dos Reis, Nawel Slama, Israel Mares-Mejía, Anne-Marie Cirinesi and 3 more

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in Nature communications, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
2.9field-weighted citation impact, top 9% of its field
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

12 citing papers in PubMed, 24 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Structural and functional determinants inferred from deep mutational scans.Protein science : a publication of the Protein Society · 2022
    Article
  7. Article
  8. Article
  9. HigB1 Toxin inFrontiers in microbiology · 2021
    Article
  10. Control of Toxin-Antitoxin Systems by Proteases inFrontiers in molecular biosciences · 2021
    Review
  11. Article
  12. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors at 1 institution in 1 country.

Valérie GuilletInstitut de Pharmacologie et de Biologie Structurale, IPBS, Université de Toulouse, CNRS, UPS, 31077, Toulouse, France.
Patricia BordesLaboratoire de Microbiologie et de Génétique Moléculaires, Centre de Biologie Intégrative (CBI), Université de Toulouse, CNRS, UPS, 31062, Toulouse, France.
Cécile BonInstitut de Pharmacologie et de Biologie Structurale, IPBS, Université de Toulouse, CNRS, UPS, 31077, Toulouse, France.
Julien MarcouxInstitut de Pharmacologie et de Biologie Structurale, IPBS, Université de Toulouse, CNRS, UPS, 31077, Toulouse, France.ORCID http://orcid.org/0000-0001-7321-7436
Virginie GervaisInstitut de Pharmacologie et de Biologie Structurale, IPBS, Université de Toulouse, CNRS, UPS, 31077, Toulouse, France.
Ambre Julie SalaLaboratoire de Microbiologie et de Génétique Moléculaires, Centre de Biologie Intégrative (CBI), Université de Toulouse, CNRS, UPS, 31062, Toulouse, France.
Suzana Dos ReisInstitut de Pharmacologie et de Biologie Structurale, IPBS, Université de Toulouse, CNRS, UPS, 31077, Toulouse, France.
Nawel SlamaLaboratoire de Microbiologie et de Génétique Moléculaires, Centre de Biologie Intégrative (CBI), Université de Toulouse, CNRS, UPS, 31062, Toulouse, France.
Israel Mares-MejíaInstitut de Pharmacologie et de Biologie Structurale, IPBS, Université de Toulouse, CNRS, UPS, 31077, Toulouse, France.
Anne-Marie CirinesiLaboratoire de Microbiologie et de Génétique Moléculaires, Centre de Biologie Intégrative (CBI), Université de Toulouse, CNRS, UPS, 31062, Toulouse, France.
Laurent MaveyraudInstitut de Pharmacologie et de Biologie Structurale, IPBS, Université de Toulouse, CNRS, UPS, 31077, Toulouse, France.ORCID http://orcid.org/0000-0003-4610-8319
Pierre GenevauxLaboratoire de Microbiologie et de Génétique Moléculaires, Centre de Biologie Intégrative (CBI), Université de Toulouse, CNRS, UPS, 31062, Toulouse, France. pierre.genevaux@ibcg.biotoul.fr.
Lionel MoureyInstitut de Pharmacologie et de Biologie Structurale, IPBS, Université de Toulouse, CNRS, UPS, 31077, Toulouse, France. lionel.mourey@ipbs.fr.ORCID http://orcid.org/0000-0002-8259-1259
Centre National de la Recherche Scientifique · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

SecB chaperones assist protein export by binding both unfolded proteins and the SecA motor. Certain SecB homologs can also control toxin-antitoxin (TA) systems known to modulate bacterial growth in response to stress. In such TA-chaperone (TAC) systems, SecB assists the folding and prevents degradation of the antitoxin, thus facilitating toxin inhibition. Chaperone dependency is conferred by a C-terminal extension in the antitoxin known as chaperone addiction (ChAD) sequence, which makes the antitoxin aggregation-prone and prevents toxin inhibition. Using TAC of Mycobacterium tuberculosis, we present the structure of a SecB-like chaperone bound to its ChAD peptide. We find differences in the binding interfaces when compared to SecB-SecA or SecB-preprotein complexes, and show that the antitoxin can reach a functional form while bound to the chaperone. This work reveals how chaperones can use discrete surface binding regions to accommodate different clients or partners and thereby expand their substrate repertoire and functions.

Indexed as

Bacterial ProteinsBinding SitesMolecular ChaperonesMycobacterium tuberculosisProtein BindingProtein Structure, SecondaryProtein Structure, TertiaryToxin-Antitoxin SystemsBacterial ProteinsMolecular Chaperones

Identifiers

PMID30770830
PMCPMC6377645
OpenAlexW2911948414

What OpenQuestion holds

Textmetadata
LicenceCC BY
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 OpenQuestion graph.