Human transferrin and lactoferrin cooperatively support <i>Neisseria meningitidis</i> colonization in the murine nasopharynx
Bibliographic record
Abstract
ABSTRACT Neisseria meningitidis is a human-restricted bacteria that is a normal nasopharyngeal resident, yet it can also disseminate, causing invasive meningococcal disease. Meningococci are highly adapted to life in humans, with human-specific virulence factors contributing to bacterial adhesion, nutrient acquisition and immune evasion. While these factors have been explored in isolation, their relative contribution during infection has not been considered due to their absence in small animal models and their expression by different human cell types not readily combined in either in vitro or ex vivo systems. Herein, we show that transgenic expression of the iron-binding glycoproteins human transferrin and lactoferrin can each facilitate N. meningitidis replication in mouse serum but that transferrin was required to support infection-induced sepsis. While these host proteins are insufficient to allow nasopharyngeal colonization alone, mice co-expressing these and human CEACAM1 support robust colonization. In this case, meningococcal colonization elicits an acute elevation in both transferrin and lactoferrin levels within the upper respiratory mucosa, with transferrin levels remaining elevated while lactoferrin returns to basal levels after establishment of infection. Competitive infection of triple transgenic animals with transferrin- and lactoferrin- binding protein mutants selects for bacteria expressing the transferrin receptor, implicating the critical contribution of transferrin-based iron acquisition to support colonization. These transgenic animals have thus allowed us to disentangle the relative contribution of three virulence factors during colonization and invasive disease, and provides a novel in vivo model that can support extended meningococcal colonization, opening a new avenue to explore the meningococcal lifestyle within its primary niche.
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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 | 0.001 |
| 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".