The microtubule networks in lung epithelia are severed during <i>Klebsiella pneumoniae</i> infections
Bibliographic record
Abstract
Klebsiella pneumoniae is an enteric bacterium known to cause pneumonia, urinary tract infections and pyogenic liver abscesses. Of these infections, patients who develop pneumonia have poor survival rates and alarming mortality rates of up to 44% in highly infected individuals. Many studies have focused on identifying bacterial components crucial to the disease process, but the underlying sub‐cellular mechanisms for disease progression have remained elusive. To begin to study these mechanisms, we assessed the cytoskeletal integrity of infected A549 lung epithelial cells and lung epithelia from infected C57Bl/6J mice. We found that the microtubule networks of the entire epithelia were either severed or fully disassembled even when there were no bacteria directly attached on the host cells. Since bacterial attachment was not necessary to cause microtubule disassembly, we hypothesized that a novel K. pneumoniae protein activates signalling cascades that target microtubule‐severing activity within these lung cells. To test this hypothesis, we first infected A549 cells with K. pneumoniae mutants deficient for known bacterially generated pathogenic proteins and found that none of those proteins triggered microtubule severing. Then, we created a genomic library of the entire K. pneumoniae genome. Out of the ~3000 known K. pneumoniae genes, we found that K. pneumoniae ytfL ( KP ytfL ) consistently triggered microtubule severing in infected A549 cells. Bioinformatic analysis showed that the C‐terminal domain of KP YtfL has a catalytic region that could activate host signalling cascades. We then sought to identify the host microtubule‐severing enzyme responsible for the epithelial cell phenotype. Through immunolocalization studies, we discovered that the katanin catalytic subunit A1 like 1 protein (KATNAL1) and the katanin regulatory subunit B1 protein (KATNB1) were at the precise sites of microtubule severing. To determine if KATNAL1 and KATNB1 were responsible for K. pneumoniae ‐induced severing, we deleted the gene for either KATNAL1 or KATNB1 in A549 cells using CRISPR. We then infected the cells and when all the infected wild type cells had disassembled microtubules, KATNAL1 and KATNB1‐deficient cells retained intact microtubules. Thus, KATNAL1 and KATNB1 contribute to the microtubule severing activity during K. pneumoniae infections. Taken together, our data indicates that KP YtfL is a novel protein effector that triggers the activation of KATNAL1 and KATNB1 to sever microtubules in infected lung epithelial cells. Through our study, we identified a novel bacterial mechanism to destabilize the microtubule networks of an entire epithelium through the activation of host cell microtubule severing enzymes. Support or Funding Information This study was funded by NSERC, Taiwan NHRI and SFU institutional funds. This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
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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) | 0.001 | 0.000 |
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.
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".