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Record W2020204572 · doi:10.1159/000320268

Determination of <i>Francisella tularensis</i> AcpB Acid Phosphatase Substrate Preferences

2010· article· en· W2020204572 on OpenAlexaff
Evan Crowe, Ricardo Valladares, Clara Vu, Ekaterina Kuznetsova, Claudio F. González

Bibliographic record

VenueMicrobial Physiology · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBacillus and Francisella bacterial research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsFrancisella tularensisFrancisellaThiamineBiochemistryPhosphataseEnzymeSubstrate (aquarium)BiologyMicrobiologyPhosphorylationPathogenIntracellularChemistryVirulenceGene

Abstract

fetched live from OpenAlex

The Francisella species encode 4 main acid phosphatases (Acp) that are potentially involved in pathogenesis through currently unknown mechanisms. Only 2 of these enzymes, AcpA and AcpC, have been biochemically characterized to date. In this work we describe the catalytic properties of Francisella tularensis AcpB utilizing an array of 120 phosphorylated substrates. In contrast to most acid phosphatases, the purified enzyme showed a narrow range of substrate preferences, with the highest affinity towards thiamine phosphate (Km = 150 μM). Francisella species do not possess a thiamine biosynthetic pathway even though vitamin B1 is indispensable in numerous cellular functions. Consequently, thiamine should be incorporated from the environment, in this case, from the host cell. Our results suggested that AcpB could provide the hydrolytic activity necessary to transform the nontransportable phosphorylated vitamin B1 present in tissues to a form that can be absorbed by the intracellular pathogen.

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)0.001
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
Metaresearch0.0000.001
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)0.0010.000

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 head0.238
Teacher spread0.229 · 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

Citations1
Published2010
Admission routes1
Has abstractyes

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