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Record W4389086573 · doi:10.1038/s41467-023-43585-5

Structural and functional insights into the delivery of a bacterial Rhs pore-forming toxin to the membrane

2023· article· en· W4389086573 on OpenAlexafffund
Amaia González‐Magaña, Igor Tascón, Jon Altuna-Alvarez, María Queralt-Martín, Jake Colautti, Carmen Velázquez, Maialen Zabala-Zearreta, Jéssica Rojas-Palomino, Marité Cárdenas, Antonio Alcaraz, John C. Whitney, Iban Ubarretxena‐Belandia, D. Albesa-Jové

Bibliographic record

VenueNature Communications · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicYersinia bacterium, plague, ectoparasites research
Canadian institutionsMcMaster University
FundersAgencia Estatal de InvestigaciónMedical Research CouncilUniversitat Jaume IEuropean Regional Development FundEuropean CommissionEuskal Herriko UnibertsitateaGeneralitat ValencianaEusko JaurlaritzaFunctional Genomics Center ZurichMinisterio de Ciencia e InnovaciónDiamond Light SourceCanadian Institutes of Health ResearchEidgenössische Technische Hochschule ZürichWellcome Trust
KeywordsMicrobial toxinsToxinChemistryMembranePore-forming toxinBiophysicsMicrobiologyBiologyBiochemistry

Abstract

fetched live from OpenAlex

Bacterial competition is a significant driver of toxin polymorphism, which allows continual compensatory evolution between toxins and the resistance developed to overcome their activity. Bacterial Rearrangement hot spot (Rhs) proteins represent a widespread example of toxin polymorphism. Here, we present the 2.45 Å cryo-electron microscopy structure of Tse5, an Rhs protein central to Pseudomonas aeruginosa type VI secretion system-mediated bacterial competition. This structural insight, coupled with an extensive array of biophysical and genetic investigations, unravels the multifaceted functional mechanisms of Tse5. The data suggest that interfacial Tse5-membrane binding delivers its encapsulated pore-forming toxin fragment to the target bacterial membrane, where it assembles pores that cause cell depolarisation and, ultimately, bacterial death.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.771
Threshold uncertainty score0.287

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.020
GPT teacher head0.298
Teacher spread0.278 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations24
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueNature CommunicationsSame topicYersinia bacterium, plague, ectoparasites researchFrench-language works237,207