A Novel Metal Transporter Mediating Manganese Export (MntX) Regulates the Mn to Fe Intracellular Ratio and Neisseria meningitidis Virulence
Bibliographic record
Abstract
Neisseria meningitidis (Nm) and N. gonorrhoeae (Ng) are adapted to different environments within their human host. If the basis of this difference has not yet been fully understood, previous studies (including our own data) have reported that, unlike Ng, Nm tolerates high manganese concentrations. As transition metals are essential regulators of cell growth and host pathogen interactions, we aimed to address mechanisms of Nm Mn²⁺ tolerance and its pathogenic consequences. Using bioinformatics, gene deletion and heterologous expression we identified a conserved bacterial manganese resistance factor MntX (formerly YebN). The predicted structure suggests that MntX represents a new family of transporters exporting Mn. In the Neisseria genus, this exporter is present and functional in all Nm isolates but it is mutated in a majority of Ng strains and commonly absent in nonpathogenic species. In Nm, Mn²⁺ export via MntX regulates the intracellular Mn/Fe ratio and protects against manganese toxicity that is exacerbated in low iron conditions. MntX is also important for N. meningitidis to resist killing by human serum and for survival in mice blood during septicemia. The present work thus points to new clues about Mn homeostasis, its interplay with Fe metabolism and the influence on N. meningitidis physiology and pathogenicity.
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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) | 0.000 | 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".