Virulence hierarchies within the <i>Mycobacterium tuberculosis</i> complex
Bibliographic record
Abstract
The Mycobacterium tuberculosis complex (MTBC) includes M. tuberculosis ( M. tb ), the primary cause of human tuberculosis, M. bovis, the classical zoonotic pathogen and cause of bovine tuberculosis, and M. orygis, a recently recognized multihost pathogen. Given that M. tb, M. bovis, and M. orygis pose significant threats to the health of humans and animals, we sought to understand fundamental differences in pathogenicity among these closely related organisms. Building upon historical observations, we conducted a comparative virulence assessment of these pathogens using both bovine and murine infection models. Holstein calves were infected via aerosol with M. tb, M. bovis, or M. orygis , and pathology was analyzed through macroscopic and microscopic assessments of lungs and lymph nodes, along with quantitative tissue bacterial burden measurements. In C57BL/6 mice, we compared virulence using three readouts, namely survival, lethal dose determination, and detailed pathological assessments. Despite genomic similarity, animal-adapted MTBCs consistently showed dramatically enhanced virulence compared to M. tb with distinct immunopathology and, in the murine model, mortality within 24 days. Using gene disruption studies guided by proteomic comparisons, we determined that these infection outcomes were dependent on shared (ESAT-6) and lineage-associated (MPT70) virulence factors, the route of infection, and prior infection or immunization. Our findings reveal unexpected virulence hierarchies within the MTBC, with fundamental and translational implications for tuberculosis research.
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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 | 0.001 | 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".