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Mutations in <i>Mycobacterium tuberculosis Rv0444c</i>, the gene encoding anti‐SigK, explain high level expression of MPB70 and MPB83 in <i>Mycobacterium bovis</i>

2006· article· en· W2021607612 on OpenAlexafffund
Battouli Saïd‐Salim, Serge Mostowy, Arnold S. Kristof, Marcel A. Behr

Bibliographic record

VenueMolecular Microbiology · 2006
Typearticle
Languageen
FieldMedicine
TopicMycobacterium research and diagnosis
Canadian institutionsMcGill UniversityMcGill University Health Centre
FundersCanadian Institutes of Health Research
KeywordsMycobacterium bovisBiologyMycobacterium tuberculosisGeneMutantTuberculosisComplementationPhenotypeMicrobiologyGeneticsMedicine

Abstract

fetched live from OpenAlex

It has recently been advanced that Mycobacterium tuberculosis sigma factor K (SigK) positively regulates expression of the antigenic proteins MPB70 and MPB83. As expression of these proteins differs between M. tuberculosis (low) and Mycobacterium bovis (high), this study set out to determine whether M. bovis lacks a functional SigK repressor (anti-SigK). By comparing genes near sigK in M. tuberculosis H37Rv and M. bovis AF2122/97, we observed that Rv0444c, annotated as unknown function, had variable sequence in M. bovis. Analysis of in vitro mpt70/mpt83 expression and Rv0444c sequencing across M. tuberculosis complex (MTC) members revealed that high-level expression was associated with a mutated Rv0444c. Complementation of M. bovis bacillus Calmette-Guerin Russia, a high producer of MPB70/MPB83, with wild-type Rv0444c resulted in a significant decrease in mpb70/mpb83 expression. Conversely, a M. tuberculosis H37Rv mutant which expressed sigK but not Rv0444c manifested the M. bovis phenotype of high-level MPB70/MPB83 expression. Further support that Rv0444c encodes the anti-SigK was obtained by yeast two-hybrid studies, where the N-terminal region of Rv0444c-encoded protein interacted with SigK. Together these findings indicate that Rv0444c encodes the regulator of SigK (RskA) and mutations in this gene explain high-level MPT70/MPT83 expression by certain MTC members.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.062
Threshold uncertainty score0.958

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.012
GPT teacher head0.246
Teacher spread0.234 · 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

Citations85
Published2006
Admission routes2
Has abstractyes

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