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Record W1988960892 · doi:10.1099/mic.0.26411-0

Foreign signal peptides can constitute a barrier to functional expression of periplasmic proteins in Haemophilus influenzae

2003· article· en· W1988960892 on OpenAlexaff
Siu Ling Lam, Shane D. Kirby, Anthony B. Schryvers

Bibliographic record

VenueMicrobiology · 2003
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAntibiotic Resistance in Bacteria
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPeriplasmic spaceNeisseria gonorrhoeaeHaemophilus influenzaeSignal peptideTransferrinMicrobiologyBiologyBiochemistryGenePeptide sequenceChemistryEscherichia coliAntibiotics

Abstract

fetched live from OpenAlex

To study the periplasmic branch of iron (ferric ion) uptake systems in Gram-negative bacteria, genetic reconstitution experiments were initiated in Haemophilus influenzae involving exchange of the periplasmic iron-binding protein. The expression of many of the heterologous periplasmic ferric-binding proteins (FbpAs) was quite limited. Transformation experiments with the fbpA gene from Neisseria gonorrhoeae yielded two colony sizes with different phenotypic characteristics. The small colonies contained the intact N. gonorrhoeae fbpA gene and were deficient in utilization of transferrin iron. The large colonies contained hybrid H. influenzae/N. gonorrhoeae fbpA genes, were proficient in transferrin iron utilization and had enhanced levels of expression of FbpA. These hybrid genes included several that encoded the mature N. gonorrhoeae FbpA with the H. influenzae signal peptide. To more fully evaluate the effect of foreign signal peptides, a series of hybrid genes were prepared that exchanged the signal peptides from H. influenzae FbpA, N. gonorrhoeae FbpA and the TEM-1 beta-lactamase. The presence of the H. influenzae leader was required for functional expression of FbpAs and was shown to dramatically increase the level of beta-lactamase activity.

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 score0.031
Threshold uncertainty score0.630

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 head0.010
GPT teacher head0.224
Teacher spread0.213 · 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

Citations2
Published2003
Admission routes1
Has abstractyes

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