Quantitative Mass Spectrometry Identifies Novel Host Binding Partners for Pathogenic <i>Escherichia coli</i> Type III Secretion System Effectors
Bibliographic record
Abstract
Enteropathogenic and enterohemorrhagic Escherichia coli cause enteric diseases resulting in significant morbidity and mortality worldwide. These pathogens remain extracellular and translocate a set of type III secreted effector proteins into host cells to promote bacterial virulence. Effectors manipulate host cell pathways to facilitate infection by interacting with a variety of host targets, yet the binding partners and mechanism of action of many effectors remain elusive. We performed a mass spectrometry screen to identify host targets for a library of effectors. We found five known effector targets and discovered four novel interactions. Interestingly, we identified multiple effectors that interacted with the microtubule associated protein, ensconsin. Using co-immunoprecipitations, we confirmed that NleB1 and EspL interacted with ensconsin in a region that corresponded to its microtubule binding domain. Ensconsin is an essential cofactor of kinesin-1 that is required for intracellular trafficking, and we demonstrated that intracellular trafficking was severely disrupted during wild type EPEC infections but not during infections with ΔnleB1 or ΔespL mutants. Our findings demonstrate the efficacy of quantitative proteomics for identifying effector-host protein interactions and suggest that vesicular trafficking is a crucial cellular process that may be targeted by NleB1 and EspL through their interaction with ensconsin.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".