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Record W1562463165 · doi:10.1111/mmi.12068

A novel iron‐ and copper‐binding protein in the <scp>L</scp>yme disease spirochaete

2012· article· en· W1562463165 on OpenAlexaff
Peng Wang, Anthony Lutton, John W. Olesik, Hojatollah Vali, Xin Li

Bibliographic record

VenueMolecular Microbiology · 2012
Typearticle
Languageen
FieldNursing
TopicTrace Elements in Health
Canadian institutionsMcGill University
FundersOhio State UniversityArthritis Foundation
KeywordsBiologySpirochaeteMetallothioneinCopperCopper toxicityMicrobiologyPathogenMutantBiochemistryBorrelia burgdorferiBacteriaGeneticsGeneChemistry

Abstract

fetched live from OpenAlex

Iron and copper are transition metals that can be toxic to cells due to their abilities to react with peroxide to generate hydroxyl radical. Ferritins and metallothioneins are known to sequester intracellular iron and copper respectively. The Lyme disease pathogen Borrelia burgdorferi does not require iron, but its genome encodes a ferritin-like Dps (DNA-binding protein from starved bacteria) molecule, which has been shown to be important for the spirochaete's persistence in the tick and subsequent transmission to a new host. Here, we show that the carboxyl-terminal cysteine-rich (CCR) domain of this protein functions as a copper-binding metallothionein. This novel fusion between Dps and metallothionein is unique to and conserved in all Borrelia species. We term this molecule BicA for Borrelia iron- and copper-binding protein A. An isogenic mutant lacking BicA had significantly reduced levels of iron and copper and was more sensitive to iron and copper toxicity than its parental strain. Supplementation of the medium with iron or copper rendered the spirochaete more susceptible to peroxide killing. These data suggest that an important function of BicA is to detoxify excess iron and copper the spirochaete may encounter during its natural life cycle through a tick vector and a vertebrate host.

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)0.001
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 score0.440
Threshold uncertainty score0.717

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.015
GPT teacher head0.268
Teacher spread0.253 · 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

Citations43
Published2012
Admission routes1
Has abstractyes

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