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Record W2593090067 · doi:10.1073/pnas.1614902114

Manganese scavenging and oxidative stress response mediated by type VI secretion system in <i>Burkholderia thailandensis</i>

2017· article· en· W2593090067 on OpenAlexafffund
Meiru Si, Chao Zhao, Brianne J. Burkinshaw, Bing Zhang, Dawei Wei, Yao Wang, Tao Dong, Xihui Shen

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVibrio bacteria research studies
Canadian institutionsUniversity of Calgary
FundersFundamental Research Funds for the Central UniversitiesAlberta InnovatesNational Natural Science Foundation of ChinaGovernment of CanadaDirectorate for Biological SciencesPurdue University
KeywordsOxidative stressManganeseSecretionScavengingChemistryMicrobiologyBiologyBiochemistryAntioxidantOrganic chemistry

Abstract

fetched live from OpenAlex

Significance As an essential micronutrient, Gram-negative bacteria must concentrate Mn 2+ into the cytosol via active transport systems to meet cellular demands. Whereas inner membrane Mn 2+ transporters have been characterized, an active transporter for translocation of Mn 2+ across the outer membrane has not been described. Here we report a Mn 2+ -scavenging pathway consisting of a newly identified TonB-dependent outer membrane manganese transporter, MnoT, and a type VI secretion system (T6SS)-secreted Mn 2+ -binding protein, TseM. Traditionally, T6SS is recognized as a contact-dependent nanomachine to inject effectors into eukaryotic or prokaryotic cells for virulence or for interbacterial competition. The contact-independent functions of T6SS for metal acquisition and bacteria–bacteria competition, reported here, suggest that T6SS may have been retrofitted by some bacteria to gain additional adaptive functions during evolution.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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 head0.025
GPT teacher head0.306
Teacher spread0.281 · 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 source (direct Gemma or distilled Codex), 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

Citations246
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueProceedings of the National Academy of SciencesSame topicVibrio bacteria research studiesFrench-language works237,207