<i>Klebsiella pneumoniae</i> reduces SUMOylation to limit host defence responses
Bibliographic record
Abstract
ABSTRACT Klebsiella pneumoniae is an important cause of multidrug resistant infections worldwide. Understanding the virulence mechanisms of K. pneumoniae is a priority and timely to design new therapeutics. Here we demonstrate that K. pneumoniae limits the SUMOylation of host proteins in epithelial cells and macrophages (mouse and human) to subvert cell innate immunity. Mechanistically, in lung epithelial cells Klebsiella increases the levels of the deSUMOylase SENP2 in the cytosol by affecting its K48-ubiquitylation and its subsequent degradation by the ubiquitin proteasome. This is dependent on Klebsiella preventing the NEDDylation of the Cullin-1 subunit of the ubiquitin ligase complex E3-SCFβ-TrCP by exploiting the CSN5 deNEDDylase. Klebsiella induces the expression of CSN5 in an EGFR-PI3K-AKT-ERK-GSK3β signalling pathway dependent manner. In macrophages, TLR4-TRAM-TRIF induced type-I IFN via IFNAR1-controlled signalling mediates Klebsiella -triggered decrease in the levels of SUMOylation via let-7 miRNAs. Our results revealed the crucial role played by Klebsiella polysaccharides, the capsule and the LPS O-polysaccharide, to decrease the levels of SUMO-conjugated proteins in epithelial cells and macrophages. Klebsiella -induced decrease in SUMOylation promotes infection by limiting the activation of inflammatory responses and increasing intracellular survival in macrophages. IMPORTANCE Klebsiella pneumoniae has been singled out as an urgent threat to human health due to the increasing isolation of strains resistant to “last line” antimicrobials, narrowing the treatment options against Klebsiella infections. Unfortunately, at present, we cannot identify candidate compounds in late-stage development for treatment of multidrug Klebsiella infections; this pathogen is exemplary of the mismatch between unmet medical needs and the current antimicrobial research and development pipeline. Furthermore, there is still limited evidence on K. pneumoniae pathogenesis at the molecular and cellular level in the context of the interactions between bacterial pathogens and their hosts. In this research, we have uncovered a sophisticated strategy employed by Klebsiella to subvert the activation of immune defences by controlling the modification of proteins. Our research may open opportunities to develop new therapeutics based on counteracting this Klebsiella- controlled immune evasion strategy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".