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The <i>Klebsiella pneumoniae</i> Gene <i>ytfL</i> Triggers Microtubule Disassembly in Lung Epithelial Cells through KATNAL1

2017· article· en· W4389019681 on OpenAlexafffund
Michael Dominic Chua, L. Kristopher Siu, Kuo‐Ming Yeh, Julian A. Guttman

Bibliographic record

VenueThe FASEB Journal · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicBacteriophages and microbial interactions
Canadian institutionsSimon Fraser University
FundersNatural Sciences and Engineering Research Council of CanadaNational Health Research Institutes
KeywordsMicrotubuleBiologyCell biologyKlebsiella pneumoniaeCytoskeletonGenePhenotypeCellMicrobiologyEscherichia coliGenetics

Abstract

fetched live from OpenAlex

The Gram‐negative bacterium Klebsiella pneumoniae can cause septicemia, pneumonia, liver abscesses, and meningitis resulting in mortality rates as high as 44%. Unfortunately, the sub‐cellular interactions of these bacteria with host cells remain poorly understood. Because many bacterial pathogens target the host cell cytoskeleton, we examined the host cell cytoskeleton of K. pneumoniae ‐infected lung epithelial cells. In this study, we focused on the host microtubule network and found that microtubules were severed by the microbes, which ultimately led to the disassembly of the entire microtubule network. Because severing of microtubules in lung epithelial cells are regulated by host cell mechanisms, we hypothesized that a K. pneumoniae gene product would trigger the microtubule severing events through the activation of a host microtubule severing protein. To test this hypothesis, we screened the known disease‐causing proteins of K. pneumoniae and found that expression of the capsular polysaccharide, outer membrane porins, and the type VI secretion system were not important for inducing microtubule severing. Next, we constructed and screened a library encompassing essentially all (~3000) K. pneumoniae genes to identify genes that could cause this phenotype. Using this library, we identified the gene KP ytfL that caused the microtubule severing phenotype. To further characterize this novel mechanism, we immunolocalized all known epithelial cell microtubule severing proteins in K. pneumoniae ‐infected cells and found that the katanin‐like protein 1 (KATNAL1) localized precisely to the sites of microtubule severing. Taken together, our study shows that K. pneumoniae exploits a novel strategy to disassemble epithelial cell microtubules during its infections. The disassembly of microtubules is initiated by the expression of the bacterial gene KP ytfL , which ultimately induces the host protein KATNAL1 to sever microtubules and disrupt the microtubule network of host cells. Support or Funding Information This study was funded by NSERC, Taiwan NHRI and SFU Funds.

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 score0.005

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.011
GPT teacher head0.247
Teacher spread0.237 · 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

Citations0
Published2017
Admission routes2
Has abstractyes

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