MétaCan
Menu
Back to cohort
Record W2102789902 · doi:10.1186/gb-2007-8-6-r102

Comparison of Francisella tularensis genomes reveals evolutionary events associated with the emergence of human pathogenic strains

2007· article· en· W2102789902 on OpenAlex
Laurence Rohmer, Christine T. Fong, Simone Abmayr, Michael Wasnick, Matthew C. Radey, Tína Guina, Kerstin Svensson, Hillary S. Hayden, Michael A. Jacobs, Larry A. Gallagher, Colin Manoil, Robert K. Ernst, Becky Drees, Danielle Buckley, Eric Haugen, Donald Bovee, Yang Zhou, Jean Chang, Ruth Levy, Will Gillett, Don Guenthener, Allison Kang, Scott A. Shaffer, Greg Taylor, Jinzhi Chen, Byron Gallis, David A. D’Argenio, Mats Forsman, Maynard V. Olson, David R. Goodlett, Rajinder Kaul, Samuel I. Miller, M. Brittnacher

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueGenome biology · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBacillus and Francisella bacterial research
Canadian institutionsnot available
FundersNational Institute of Allergy and Infectious DiseasesU.S. Public Health ServiceUniversity of Victoria
KeywordsBiologyFrancisella tularensisHuman geneticsGenomeEvolutionary biologyFrancisellaGenome BiologyGeneticsTularemiaComparative genomicsGenomicsComputational biologyGeneVirologyVirulence

Abstract

fetched live from OpenAlex

BACKGROUND: Francisella tularensis subspecies tularensis and holarctica are pathogenic to humans, whereas the two other subspecies, novicida and mediasiatica, rarely cause disease. To uncover the factors that allow subspecies tularensis and holarctica to be pathogenic to humans, we compared their genome sequences with the genome sequence of Francisella tularensis subspecies novicida U112, which is nonpathogenic to humans. RESULTS: Comparison of the genomes of human pathogenic Francisella strains with the genome of U112 identifies genes specific to the human pathogenic strains and reveals pseudogenes that previously were unidentified. In addition, this analysis provides a coarse chronology of the evolutionary events that took place during the emergence of the human pathogenic strains. Genomic rearrangements at the level of insertion sequences (IS elements), point mutations, and small indels took place in the human pathogenic strains during and after differentiation from the nonpathogenic strain, resulting in gene inactivation. CONCLUSION: The chronology of events suggests a substantial role for genetic drift in the formation of pseudogenes in Francisella genomes. Mutations that occurred early in the evolution, however, might have been fixed in the population either because of evolutionary bottlenecks or because they were pathoadaptive (beneficial in the context of infection). Because the structure of Francisella genomes is similar to that of the genomes of other emerging or highly pathogenic bacteria, this evolutionary scenario may be shared by pathogens from other species.

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.

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)0.001
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 score0.755
Threshold uncertainty score0.462

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.028
GPT teacher head0.322
Teacher spread0.294 · 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