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Record W4315864851 · doi:10.1038/s41467-023-35897-3

Coupled induction of prophage and virulence factors during tick transmission of the Lyme disease spirochete

2023· article· en· W4315864851 on OpenAlexaff
Jenny Wachter, Britney Cheff, C. Hillman, Valentina Carracoi, David W. Dorward, Craig Martens, Kent Barbian, Glenn Nardone, L. Renee Olano, Margie Kinnersley, Patrick R. Secor, Patricia A. Rosa

Bibliographic record

VenueNature Communications · 2023
Typearticle
Languageen
FieldImmunology and Microbiology
TopicVector-borne infectious diseases
Canadian institutionsUniversity of Saskatchewan
FundersNational Institute of Allergy and Infectious DiseasesNational Institute of General Medical SciencesNational Institutes of Health
KeywordsrpoSProphageBorrelia burgdorferiBiologyLysogenic cycleMicrobiologySigma factorLytic cyclePlasmidGeneVirulenceVirologyBacteriophageGene expressionGeneticsPromoterVirusEscherichia coliAntibody

Abstract

fetched live from OpenAlex

The alternative sigma factor RpoS plays a central role in the critical host-adaptive response of the Lyme disease spirochete, Borrelia burgdorferi. We previously identified bbd18 as a negative regulator of RpoS but could not inactivate bbd18 in wild-type spirochetes. In the current study we employed an inducible bbd18 gene to demonstrate the essential nature of BBD18 for viability of wild-type spirochetes in vitro and at a unique point in vivo. Transcriptomic analyses of BBD18-depleted cells demonstrated global induction of RpoS-dependent genes prior to lysis, with the absolute requirement for BBD18, both in vitro and in vivo, circumvented by deletion of rpoS. The increased expression of plasmid prophage genes and the presence of phage particles in the supernatants of lysing cultures indicate that RpoS regulates phage lysis-lysogeny decisions. Through this work we identify a mechanistic link between endogenous prophages and the RpoS-dependent adaptive response of the Lyme disease spirochete.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.846
Threshold uncertainty score0.258

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 head0.015
GPT teacher head0.266
Teacher spread0.251 · 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 designBench or experimental
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

Citations28
Published2023
Admission routes1
Has abstractyes

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