The evolution of the pathogen «Mycobacterium avium» subsp «paratuberculosis»
Bibliographic record
Abstract
The genus Mycobacterium is best recognized for its pathogens M. tuberculosis and M. leprae, the etiologic agents of Tuberculosis and Leprosy. Sequencing of their genomes has revealed an evolutionary process of reductive genomics. Another common species, the M. avium complex (MAC), consists of both environmental isolates that can cause opportunistic infection in humans as well as pathogenic isolates that cause disease primarily in birds and livestock. The basis of this variation in disease phenotypes is unknown. Two genome sequences representing a pathogen of cattle, M. avium subsp. paratuberculosis (MAP) and an opportunistic isolate from a human (M. avium subsp. hominissuis) have served as the foundation for the comparative genomics of MAC. This is complicated by a level of genetic variability one log greater than found within the M. tuberculosis complex (MTBC), and by the existence of other MAC subsets beyond the two sequenced strains. In this thesis, I set out to define the phylogenetic relationships of the various members of MAC and explore the evolutionary processes that led to the emergence of the pathogenic species MAP. An identification scheme was developed to unambiguously brand subsets of MAC, a tool lacking in the past thus hampering data interpretation. Expansion to a multilocus sequence analysis (MLSA) system revealed that the MAC consists of a highly variable group with most of the genotypes belonging to what is considered to be the environmental subset. However, both the avian and MAP pathogens manifested as two separate clones that have independently evolved from their larger subset. The distribution and directionality (insertion or deletion) of large se
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".