Insights into <i>irr</i> and <i>rirA</i> gene regulation on the virulence of <i>Brucella melitensis</i> M5-90
Bibliographic record
Abstract
Iron is a fundamental element required by most organisms, including Brucella. Several researchers have suggested that the iron response regulator (irr) and rhizobial iron regulator (rirA) genes regulate iron acquisition by Brucella abortus, influencing heme synthesis by and virulence of this pathogen. However, little is known about another Brucella species, Brucella melitensis. In this research, we successfully constructed two mutants: M5-90Δirr and M5-90ΔrirA. The adhesion, invasion, and intracellular survivability of these two mutants were evaluated in RAW264.7 cells infected with 1 × 106 CFU of M5-90Δirr, M5-90ΔrirA, or M5-90. We also tested the sensitivity of cells to hydrogen peroxide and their ability to grow. In addition, the virulence of these two mutants was evaluated in BALB/c mice. The results showed that the ability of these two mutants to invade and adhere inside the murine macrophages RAW264.7 was attenuated but their ability to replicate intracellularly was strengthened, enhancing the resistance to hydrogen peroxide. The M5-90Δirr mutant showed stronger growth ability than the parental strain under iron-limiting conditions. No differences were observed in the number of bacteria in spleen between M5-90 and M5-90Δirr at 7 or 15 days postinfection. However, the number of M5-90ΔrirA in spleen reduced significantly at 15 days postinfection. The splenic index of the M5-90Δirr group is evidently lower than that of M5-90. This is the first report that irr and rirA genes of B. melitensis are associated not only with virulence but also with growth ability. Together, our data suggest that M5-90Δirr is a promising Brucella vaccine candidate.
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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".