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Record W4410778848 · doi:10.1128/mbio.00775-25

Targeting the MEK1/2 pathway to combat <i>Staphylococcus aureus</i> infection and inflammation in cystic fibrosis

2025· article· en· W4410778848 on OpenAlexaff
Eryn Zuiker, Gregory Serpa, Mithu De, Yiwei Liu, Daniel J. Wozniak, Kymberly M. Gowdy, Jean Charron, Susan E. Birket, Megan R. Kiedrowski, Emily A. Hemann, Matthew E. Long

Bibliographic record

VenuemBio · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAntibiotic Resistance in Bacteria
Canadian institutionsUniversité LavalCentre hospitalier universitaire de Québec
FundersNational Center for Advancing Translational SciencesNational Institute of Allergy and Infectious DiseasesNational Cancer InstituteNational Institutes of HealthCystic Fibrosis Foundation
KeywordsStaphylococcus aureusMicrobiologyTLR2InflammationCystic fibrosisMethicillin-resistant Staphylococcus aureusSecretionMedicineStaphylococcal Skin InfectionsIn vivoImmunologyBiologyBacteriaInternal medicine

Abstract

fetched live from OpenAlex

ABSTRACT Staphylococcus aureus infections remain an ongoing challenge for people with cystic fibrosis (PwCF), with the increased global prevalence of multidrug-resistant strains requiring new therapeutic approaches. Our previous studies demonstrated anti-inflammatory effects of several MEK1/2 inhibitor compounds, including PD0325901, CI-1040, and trametinib, in human phagocytes from PwCF and a murine S. aureus pulmonary infection model (M. De, G. Serpa, E. Zuiker, K. B. Hisert, et al., Front Cell Infect Microbiol 14:1275940, 2024, https://doi.org/10.3389/fcimb.2024.1275940 ). A recently developed MEK1/2 inhibitor compound, ATR-002, has been recognized for its ability to exert direct antibacterial effects on gram-positive bacterial species, including S. aureus (C. Bruchhagen, M. Jarick, C. Mewis, T. Hertlein, et al., Sci Rep 8:9114, 2018, https://doi.org/10.1038/s41598-018-27445-7 ). However, whether ATR-002 elicits antibacterial effects on clinically relevant strains of S. aureus or anti-inflammatory effects is unknown. In this study, the effects of ATR-002 on human CF macrophage TLR2-induced pro-inflammatory cytokine secretion were evaluated, demonstrating that ATR-002 reduced TNF-α and IL-8 secretion induced by the TLR2 agonists FSL-1 or Pam3CSK4. The antibacterial effects of ATR-002 were evaluated by minimum inhibitory concentration testing using S. aureus clinical isolates obtained from PwCF. Utilization of a murine methicillin-resistant S. aureus (MRSA) pulmonary infection model further confirmed the in vivo anti-inflammatory and antibacterial effects of ATR-002. Finally, infection of wild-type and Mek2 KO mice revealed that loss of MEK2 was host-protective during MRSA pulmonary infection by reducing neutrophil-mediated inflammation without altering bacterial clearance. In summary, this study highlights the therapeutic potential of targeting the MEK1/2 pathway to combat MRSA pulmonary infections. IMPORTANCE Staphylococcus aureus infections pose a significant burden on global healthcare systems. Community-associated transmission of methicillin-resistant S. aureus (MRSA) and the increasing prevalence of other drug-resistant S. aureus isolates limit therapeutic options to combat this opportunistic pathogen. Infection-induced inflammation is a significant driver of tissue damage, especially in cystic fibrosis pulmonary infections. However, therapeutic strategies that can reduce inflammation without compromising host defense and bacterial clearance mechanisms are lacking. This study investigates the dual anti-inflammatory and antibacterial effects of a MEK1/2 inhibitor as a therapeutic strategy to target both host and pathogen with a single compound. This work also identifies host MEK2 as a specific target that can be modulated to reduce inflammation without impairing host defense against MRSA pulmonary infection. Results from this study can inform future human clinical trials to evaluate the ability of the MEK1/2 inhibitor compound ATR-002 to both combat S. aureus infections and reduce inflammation that accompanies these infections.

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 score0.263
Threshold uncertainty score0.302

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 integrity0.0000.000
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 head0.004
GPT teacher head0.223
Teacher spread0.220 · 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

Citations3
Published2025
Admission routes1
Has abstractyes

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