Bacterial Genetic Signatures of Human Social Phenomena among M. tuberculosis from an Aboriginal Canadian Population
Bibliographic record
Abstract
Despite a widespread global distribution and highly variable disease phenotype, there is little DNA sequence diversity among isolates of Mycobacterium tuberculosis. In addition, many regional population genetic surveys have revealed a stereotypical structure in which a single clone, lineage, or clade makes up the majority of the population. It is often assumed that dominant clones are highly adapted, that is, the overall structure of M. tuberculosis populations is the result of positive selection. In order to test this assumption, we analyzed genetic data from extant populations of bacteria circulating in Aboriginal communities in Saskatchewan, Canada. Demographic parameters of the bacterial population were estimated from archival epidemiological data collected over approximately 130 years since the onset of epidemic tuberculosis in the host communities. Bacterial genetic data were tested against neutral theory expectations and the local evolutionary history of M. tuberculosis investigated by phylogenetic analysis. Our findings are not consistent with positive selection on the bacterial population. Instead, we uncovered founder effects persisting over decades and barriers to gene flow within the bacterial population. Simulation experiments suggested that a combination of these neutral influences could result in the stereotypical structure of M. tuberculosis populations. Some aspects of population structure were suggestive of background selection, and data were on the whole consistent with combined effects of population bottlenecks, subdivision, and background selection. Neutral phenomena, namely, bottlenecks and partitions within populations, are prominent influences on the evolution of M. tuberculosis and likely contribute to restricted genetic diversity observed within this species. Given these influences, a complex evolutionary model will be required to define the relative fitness of different M. tuberculosis lineages and, ultimately, to uncover the genetic basis for its success as a pathogen.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".