Functional characterization and Me<sup>2+</sup> ion specificity of a Ca<sup>2+</sup>–citrate transporter from <i>Enterococcus faecalis</i>
Bibliographic record
Abstract
Secondary transporters of the bacterial CitMHS family transport citrate in complex with a metal ion. Different members of the family are specific for the metal ion in the complex and have been shown to transport Mg(2+)-citrate, Ca(2+)-citrate or Fe(3+)-citrate. The Fe(3+)-citrate transporter of Streptococcus mutans clusters on the phylogenetic tree on a separate branch with a group of transporters found in the phylum Firmicutes which are believed to be involved in anaerobic citrate degradation. We have cloned and characterized the transporter from Enterococcus faecalis EfCitH in this cluster. The gene was functionally expressed in Escherichia coli and studied using right-side-out membrane vesicles. The transporter catalyzes proton-motive-force-driven uptake of the Ca(2+)-citrate complex with an affinity constant of 3.5 microm. Homologous exchange is catalyzed with a higher efficiency than efflux down a concentration gradient. Analysis of the metal ion specificity of EfCitH activity in right-side-out membrane vesicles revealed a specificity that was highly similar to that of the Bacillus subtilis Ca(2+)-citrate transporter in the same family. In spite of the high sequence identity with the S. mutans Fe(3+)-citrate transporter, no transport activity with Fe(3+) (or Fe(2+)) could be detected. The transporter of E. faecalis catalyzes translocation of citrate in complex with Ca(2+), Sr(2+), Mn(2+), Cd(2+) and Pb(2+) and not with Mg(2+), Zn(2+), Ni(2+) and Co(2+). The specificity appears to correlate with the size of the metal ion in the complex.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".