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Record W4383554928 · doi:10.1016/j.celrep.2023.112781

Structure and assembly of type VI secretion system cargo delivery vehicle

2023· article· en· W4383554928 on OpenAlexaff
Wenbo He, Ke Wu, Zhenlin Ouyang, Yixin Bai, Wen Luo, Di Wu, Hao An, Yu-cheng Guo, Min Jiao, Qian Qin, Jiaxin Zhang, Yi Wu, Junjun She, Peter M. Hwang, Fang Zheng, Li Zhu, Yurong Wen

Bibliographic record

VenueCell Reports · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVibrio bacteria research studies
Canadian institutionsUniversity of Alberta
FundersChina Postdoctoral Science FoundationNatural Science Foundation of Shaanxi ProvinceNational Natural Science Foundation of ChinaLanzhou University
KeywordsTrimerType VI secretion systemRandom hexamerChemistryBiophysicsSecretionEffectorCell biologyNanotechnologyCrystallographyMaterials scienceBiologyBiochemistry

Abstract

fetched live from OpenAlex

Type VI secretion system is widely used in Gram-negative bacteria for injecting toxic effectors into neighboring prokaryotic or eukaryotic cells. Various effectors can be loaded onto the T6SS delivery tube via its core components: Hcp, VgrG, or PAAR. Here, we report 2.8-Å resolution cryo-EM structure of intact T6SS Hcp5-VgrG-PAAR cargo delivery system and crystal structure of unbound Hcp5 from B. fragilis NCTC 9343. Loading of Hcp5 hexameric ring onto VgrG causes expansion of its inner cavity and external surface, explaining how structural changes could be propagated to regulate co-polymerization and surrounding contractile sheath. High-affinity binding between Hcp and VgrG causes entropically unfavorable structuring of long loops. Furthermore, interactions between VgrG trimer and Hcp hexamer are asymmetric, with three of the six Hcp monomers exhibiting a major loop flip. Our study provides insights into the assembly, loading, and firing of T6SS nanomachine that contributes to bacterial inter-species competition and host interactions.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.264

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 science0.0000.000
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 head0.009
GPT teacher head0.242
Teacher spread0.233 · 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

Citations32
Published2023
Admission routes1
Has abstractyes

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