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Record W2921715879 · doi:10.1021/acschembio.8b01066

A Chemical Inhibitor of Cell Growth Reduces Cell Size in <i>Bacillus subtilis</i>

2019· article· en· W2921715879 on OpenAlexafffund
Scott McAuley, Stephen Vadia, Charul Jani, Alan Huynh, Zhizhou Yang, Petra Anne Levin, Justin R. Nodwell

Bibliographic record

VenueACS Chemical Biology · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBacterial Genetics and Biotechnology
Canadian institutionsMcMaster UniversityUniversity of Toronto
FundersNational Institute of General Medical SciencesCanadian Institutes of Health Research
KeywordsBacillus subtilisFtsZCell growthCell envelopeCell biologyCell divisionCellBiologyLipid IIBacterial cell structureCell membraneBiochemistryCell cycleSmall moleculeBacteriaChemistryBiophysicsEscherichia coliGeneGenetics

Abstract

fetched live from OpenAlex

Bacteria exhibit complex responses to biologically active small molecules. These responses include reductions in transcriptional and translational efficiency, alterations in metabolic flux, and in some cases, dramatic changes in growth and morphology. Here, we describe Min-1, a novel small molecule that inhibits growth of Gram-positive bacteria by targeting the cell envelope. Subinhibitory levels of Min-1 inhibits sporulation in Streptomyces venezuelae and reduces growth rate and cell length in Bacillus subtilis. The effect of Min-1 on B. subtilis cell length is significant at high growth rates sustained by nutrient-rich media but drops off when growth rate is reduced during growth on less energy-rich carbon sources. In each medium, Min-1 has no impact on the proportion of cells containing FtsZ-rings, suggesting that Min-1 reduces the mass at which FtsZ assembly is initiated. The effect of Min-1 on size is independent of UDP-glucose, which couples cell division to carbon availability, and the alarmone ppGpp, which reduces cell size via its impact on fatty acid synthesis. Min-1 activates the LiaRS stress response, which is sensitive to disruptions in the lipid II cycle and the cell membrane, and also compromises cell membrane integrity. Therefore, this novel synthetic molecule inhibits growth at high concentrations and induces a short-cell phenotype at subinhibitory concentrations that is independent of known systems that influence cell length, highlighting the complex interactions between small molecules and cell morphology.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.958

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 integrity0.0010.000
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 head0.004
GPT teacher head0.197
Teacher spread0.193 · 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

Citations12
Published2019
Admission routes2
Has abstractyes

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