MétaCan
Menu
Back to cohort
Record W2254896924 · doi:10.1186/s12864-015-2234-5

Phylogenomic exploration of the relationships between strains of Mycobacterium avium subspecies paratuberculosis

2016· article· en· W2254896924 on OpenAlexafffund
Josephine M. Bryant, Virginie Thibault, David G. Smith, Joyce McLuckie, I Héron, Iker A. Sevilla, Franck Biet, Simon R. Harris, Duncan J. Maskell, Stephen D. Bentley, Julian Parkhill, Karen Stevenson

Bibliographic record

VenueBMC Genomics · 2016
Typearticle
Languageen
FieldMedicine
TopicMycobacterium research and diagnosis
Canadian institutionsInstitute of Infection and Immunity
FundersRijksinstituut voor Volksgezondheid en MilieuScotland’s Rural CollegeQueen's UniversityUniversity of ThessalyEuropean CommissionScottish GovernmentInstitut National de la Recherche AgronomiqueRural and Environment Science and Analytical Services DivisionEusko JaurlaritzaCork Institute of TechnologyAgResearchWellcome TrustWellcome
KeywordsBiologyGeneticsGenotypingPhylogenetic treeParatuberculosisGenomePhylogeneticsWhole genome sequencingGenetic diversitySingle-nucleotide polymorphismTypingEvolutionary biologyMycobacterium avium subspecies paratuberculosisSubspeciesGenotypeMycobacteriumGenePopulationZoology

Abstract

fetched live from OpenAlex

BACKGROUND: Mycobacterium avium subspecies paratuberculosis (Map) is an infectious enteric pathogen that causes Johne's disease in livestock. Determining genetic diversity is prerequisite to understanding the epidemiology and biology of Map. We performed the first whole genome sequencing (WGS) of 141 global Map isolates that encompass the main molecular strain types currently reported. We investigated the phylogeny of the Map strains, the diversity of the genome and the limitations of commonly used genotyping methods. RESULTS: Single nucleotide polymorphism (SNP) and phylogenetic analyses confirmed two major lineages concordant with the former Type S and Type C designations. The Type I and Type III strain groups are subtypes of Type S, and Type B strains are a subtype of Type C and not restricted to Bison species. We found that the genome-wide SNPs detected provided greater resolution between isolates than currently employed genotyping methods. Furthermore, the SNP used for IS1311 typing is not informative, as it is likely to have occurred after Type S and C strains diverged and does not assign all strains to the correct lineage. Mycobacterial Interspersed Repetitive Unit-Variable Number Tandem Repeat (MIRU-VNTR) differentiates Type S from Type C but provides limited resolution between isolates within these lineages and the polymorphisms detected do not necessarily accurately reflect the phylogenetic relationships between strains. WGS of passaged strains and coalescent analysis of the collection revealed a very high level of genetic stability, with the substitution rate estimated to be less than 0.5 SNPs per genome per year. CONCLUSIONS: This study clarifies the phylogenetic relationships between the previously described Map strain groups, and highlights the limitations of current genotyping techniques. Map isolates exhibit restricted genetic diversity and a substitution rate consistent with a monomorphic pathogen. WGS provides the ultimate level of resolution for differentiation between strains. However, WGS alone will not be sufficient for tracing and tracking Map infections, yet importantly it can provide a phylogenetic context for affirming epidemiological connections.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.203
Threshold uncertainty score0.321

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 head0.108
GPT teacher head0.294
Teacher spread0.186 · 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

Citations87
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueBMC GenomicsSame topicMycobacterium research and diagnosisFrench-language works237,207