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Record W2018581198 · doi:10.1128/jvi.01410-14

Ebola Virus Modulates Transforming Growth Factor β Signaling and Cellular Markers of Mesenchyme-Like Transition in Hepatocytes

2014· article· en· W2018581198 on OpenAlexaff
Jason Kindrachuk, Victoria Wahl‐Jensen, David Safronetz, Brett Trost, Thomas Hoenen, Ryan J. Arsenault, Friederike Feldmann, Dawn Traynor, Elena Postnikova, Anthony Kusalik, Scott Napper, Joseph E. Blaney, Heinz Feldmann, Peter B. Jahrling

Bibliographic record

VenueJournal of Virology · 2014
Typearticle
Languageen
FieldMedicine
TopicViral Infections and Outbreaks Research
Canadian institutionsUniversity of Saskatchewan
FundersNational Institute of Allergy and Infectious DiseasesNational Institutes of Health
KeywordsKinomeBiologyDownregulation and upregulationSignal transductionCell biologyTransforming growth factor betaTransforming growth factorCancer researchImmunologyGenetics

Abstract

fetched live from OpenAlex

UNLABELLED: Ebola virus (EBOV) causes a severe hemorrhagic disease in humans and nonhuman primates, with a median case fatality rate of 78.4%. Although EBOV is considered a public health concern, there is a relative paucity of information regarding the modulation of the functional host response during infection. We employed temporal kinome analysis to investigate the relative early, intermediate, and late host kinome responses to EBOV infection in human hepatocytes. Pathway overrepresentation analysis and functional network analysis of kinome data revealed that transforming growth factor (TGF-β)-mediated signaling responses were temporally modulated in response to EBOV infection. Upregulation of TGF-β signaling in the kinome data sets correlated with the upregulation of TGF-β secretion from EBOV-infected cells. Kinase inhibitors targeting TGF-β signaling, or additional cell receptors and downstream signaling pathway intermediates identified from our kinome analysis, also inhibited EBOV replication. Further, the inhibition of select cell signaling intermediates identified from our kinome analysis provided partial protection in a lethal model of EBOV infection. To gain perspective on the cellular consequence of TGF-β signaling modulation during EBOV infection, we assessed cellular markers associated with upregulation of TGF-β signaling. We observed upregulation of matrix metalloproteinase 9, N-cadherin, and fibronectin expression with concomitant reductions in the expression of E-cadherin and claudin-1, responses that are standard characteristics of an epithelium-to-mesenchyme-like transition. Additionally, we identified phosphorylation events downstream of TGF-β that may contribute to this process. From these observations, we propose a model for a broader role of TGF-β-mediated signaling responses in the pathogenesis of Ebola virus disease. IMPORTANCE: Ebola virus (EBOV), formerly Zaire ebolavirus, causes a severe hemorrhagic disease in humans and nonhuman primates and is the most lethal Ebola virus species, with case fatality rates of up to 90%. Although EBOV is considered a worldwide concern, many questions remain regarding EBOV molecular pathogenesis. As it is appreciated that many cellular processes are regulated through kinase-mediated phosphorylation events, we employed temporal kinome analysis to investigate the functional responses of human hepatocytes to EBOV infection. Administration of kinase inhibitors targeting signaling pathway intermediates identified in our kinome analysis inhibited viral replication in vitro and reduced EBOV pathogenesis in vivo. Further analysis of our data also demonstrated that EBOV infection modulated TGF-β-mediated signaling responses and promoted "mesenchyme-like" phenotypic changes. Taken together, these results demonstrated that EBOV infection specifically modulates TGF-β-mediated signaling responses in epithelial cells and may have broader implications in EBOV pathogenesis.

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 score0.042
Threshold uncertainty score0.298

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.014
GPT teacher head0.269
Teacher spread0.254 · 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

Citations53
Published2014
Admission routes1
Has abstractyes

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