Population genomics provides insights into the evolution and adaptation to humans of the waterborne pathogen Mycobacterium kansasii
Bibliographic record
Abstract
Mycobacterium kansasii can cause serious pulmonary disease. It belongs to a group of closely-related species of non-tuberculous mycobacteria known as the M. kansasii complex (MKC). Here, we report a population genomics analysis of 358 MKC isolates from worldwide water and clinical sources. We find that recombination, likely mediated by distributive conjugative transfer, has contributed to speciation and on-going diversification of the MKC. Our analyses support municipal water as a main source of MKC infections. Furthermore, nearly 80% of the MKC infections are due to closely-related M. kansasii strains, forming a main cluster that apparently originated in the 1900s and subsequently expanded globally. Bioinformatic analyses indicate that several genes involved in metabolism (e.g., maintenance of the methylcitrate cycle), ESX-I secretion, metal ion homeostasis and cell surface remodelling may have contributed to M. kansasii's success and its ongoing adaptation to the human host.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".