The Impact of Genome Region of Difference 4 (RD4) on Mycobacterial Virulence and BCG Efficacy
Bibliographic record
Abstract
Comparative genome analyses have revealed a number of regions of difference (RD) among mycobacterial species. The functional consequences of most of these genome variations have not been studied. RD4, which encompasses Rv1506c-Rv1516c of Mycobacterium tuberculosis (M. tb) H37Rv, is absent in the closely related Mycobacterium bovis and M. bovis Bacille Calmette-Guérin (BCG). On the other hand, we previously found that Mycobacterium marinum has an extended RD4 which includes a number of genes involved in the biosynthesis of lipooligosaccharides (LOSs). As such, there appears to be a gradual decay of RD4 in mycobacterial genomes in the order of M. marinum, M. tb, and M. bovis (including BCG). To understand the potential effect of RD4 on mycobacterial virulence, in this study, we cloned the entire (Rv1501-1516c) and partial (Rv1501-1508c) RD4 into an integrating vector. These constructs were introduced to M. bovis BCG and M. marinum and the virulence of the RD4 knock-in strains were evaluated in the SCID mice and zebrafish infection models, respectively. BCG containing the entire RD4 exhibited similar levels of virulence to the parental strain but BCG containing partial RD4 (Rv1501-Rv1508c) was more attenuated. Similarly, zebrafish infection experiments showed that addition of partial RD4 also appeared to attenuate the virulence of M. marinum. However, M. marinum containing entire RD4 was more virulent than the wild type strain. Interestingly, BCG strains containing the entire or partial RD4 exhibited better protection of zebrafish against M. marinum challenge than the parental BCG. Taken together, our data suggest that RD4 plays a role in mycobacterial virulence and that RD4 knock-in BCG strains confer improved protection. Our study has provided new insights into the biological function of RD4 and evolution of mycobacterial genomes.
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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".