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Record W2102302276 · doi:10.1093/molbev/msp261

Bacterial Genetic Signatures of Human Social Phenomena among M. tuberculosis from an Aboriginal Canadian Population

2009· article· en· W2102302276 on OpenAlexaffabout
Caitlin S. Pepperell, Vernon Hoeppner, Mikhail Lipatov, Wendy Wobeser, Gary K. Schoolnik, Marcus W. Feldman

Bibliographic record

VenueMolecular Biology and Evolution · 2009
Typearticle
Languageen
FieldMedicine
TopicTuberculosis Research and Epidemiology
Canadian institutionsQueen's UniversityUniversity of Saskatchewan
FundersNational Institute of Allergy and Infectious DiseasesNational Institute of General Medical SciencesBinghamton UniversityNational Institutes of Health
KeywordsBiologyPopulationEvolutionary biologyGenetic diversityLineage (genetic)Selection (genetic algorithm)Phylogenetic treeCladeGenetic driftTuberculosisGenetic structureGeneticsGenetic variationDemographyGene

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.528
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.008
GPT teacher head0.321
Teacher spread0.313 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations49
Published2009
Admission routes2
Has abstractyes

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