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Record W2915546597 · doi:10.1101/559138

Growth Phase Dependent Chromosome Condensation and H-NS Protein Redistribution in <i>E. coli</i> Under Osmotic Stress

2019· preprint· en· W2915546597 on OpenAlexafffund
Nafiseh Rafiei, Martha Cordova, William Wiley Navarre, Joshua N. Milstein

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2019
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBacterial Genetics and Biotechnology
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsOsmotic shockrpoSDNA gyraseNucleoidOsmotic concentrationSigma factorPremature chromosome condensationSodiumBiophysicsChemistryOsmotic pressureBacillus subtilisBiologyCell biologyBiochemistryEscherichia coliGeneGeneticsBacteriaChromosomeGene expressionPromoterRNA polymerase

Abstract

fetched live from OpenAlex

Abstract The heat-stable nucleoid-structuring (H-NS) protein is a global transcriptional regulator implicated in coordinating the expression of over 200 genes in E. coli bacteria. We have applied super-resolved microscopy to quantify the intracellular, spatial reorganization of H-NS in response to osmotic stress. We find that H-NS shows a growth phase dependent response to hyperosmotic shock. In stationary phase, H-NS detaches from a tightly compacted bacterial chromosome and is excluded from the nucleoid volume over an extended period of time. This behaviour is absent during rapid growth but may be induced by exposing the osmotically stressed culture to the DNA gyrase inhibitor, coumermycin. This compaction/H-NS exclusion phenomenon occurs in the presence of either potassium or sodium ions and is independent of the stress responsive sigma factor RpoS, or the H-NS paralog StpA.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.008
GPT teacher head0.217
Teacher spread0.208 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2019
Admission routes2
Has abstractyes

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