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Record W4305015488 · doi:10.1186/s13071-022-05446-w

Combining deep sequencing and conventional molecular approaches reveals broad diversity and distribution of fleas and Bartonella in rodents and shrews from Arctic and Subarctic ecosystems

2022· article· en· W4305015488 on OpenAlexafffundabout
Kayla J. Buhler, Champika Fernando, Janet E. Hill, Terry D. Galloway, Suzanne Carrière, Heather Fenton, Dominique Fauteux, Emily Jenkins

Bibliographic record

VenueParasites & Vectors · 2022
Typearticle
Languageen
FieldImmunology and Microbiology
TopicBartonella species infections research
Canadian institutionsCanadian Museum of NatureGovernment of Northwest TerritoriesUniversity of ManitobaUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of CanadaW. Garfield Weston FoundationPolar Knowledge CanadaArcticNetNorth Carolina State University
KeywordsBiologyBartonellaEcologyEntomologyArcticDiversity (politics)ParasitologyZoologyGenetics

Abstract

fetched live from OpenAlex

BACKGROUND: Bartonella are intracellular bacteria that are transmitted via animal scratches, bites and hematophagous arthropods. Rodents and their associated fleas play a key role in the maintenance of Bartonella worldwide, with > 22 species identified in rodent hosts. No studies have addressed the occurrence and diversity of Bartonella species and vectors for small mammals in Arctic and Subarctic ecosystems, which are increasingly impacted by invasive species and climate change. METHODS: In this study, we characterized the diversity of rodent fleas using conventional PCR targeting the mitochondrial cytochrome c oxidase II gene (COII) and Bartonella species in rodents and shrews (n = 505) from northern Canada using conventional PCR targeting the ITS (intergenic transcribed spacer) region and gltA (citrate synthase) gene. Metagenomic sequencing of a portion of the gltA gene was completed on a subset of 42 rodents and four rodent flea pools. RESULTS: Year, total summer precipitation the year prior to sampling, average minimum spring temperature and small mammal species were significant factors in predicting Bartonella positivity. Occurrence based on the ITS region was more than double that of the gltA gene and was 34% (n = 349) in northern red-backed voles, 35% (n = 20) in meadow voles, 37% (n = 68) in deer mice and 31% (n = 59) in shrews. Six species of Bartonella were identified with the ITS region, including B. grahamii, B. elizabethae, B. washoensis, Candidatus B. rudakovii, B. doshiae, B. vinsonii subsp. berkhoffii and subsp. arupensis. In addition, 47% (n = 49/105) of ITS amplicons had < 97% identity to sequences in GenBank, possibly due to a limited reference library or previously unreported species. An additional Bartonella species (B. heixiaziensis) was detected during metagenomic sequencing of the gltA gene in 6/11 rodents that had ITS sequences with < 97% identity in GenBank, highlighting that a limited reference library for the ITS marker likely accounted for low sequence similarity in our specimens. In addition, one flea pool from a northern red-backed vole contained multiple species (B. grahamii and B. heixiaziensis). CONCLUSION: Our study calls attention to the usefulness of a combined approach to determine the occurrence and diversity of Bartonella communities in hosts and vectors.

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 score0.043
Threshold uncertainty score0.634

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.029
GPT teacher head0.242
Teacher spread0.213 · 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

Citations7
Published2022
Admission routes3
Has abstractyes

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