Distribution of PDLIM1 at actin‐rich structures generated by invasive and adherent bacterial pathogens
Bibliographic record
Abstract
The enteric bacterial pathogens Listeria monocytogenes (Listeria) and enteropathogenic Escherichia coli (EPEC) remodel the eukaryotic actin cytoskeleton during their disease processes. Listeria generate slender actin-rich comet/rocket tails to move intracellularly, and later, finger-like membrane protrusions to spread amongst host cells. EPEC remain extracellular, but generate similar actin-rich membranous protrusions (termed pedestals) to move atop the host epithelia. These structures are crucial for disease as diarrheal (and systemic) infections are significantly abrogated during infections with mutant strains that are unable to generate the structures. The current repertoire of host components enriched within these structures is vast and diverse. In this protein catalog, we and others have found that host actin crosslinkers, such as palladin and α-actinin-1, are routinely exploited. To expand on this list, we set out to investigate the distribution of PDLIM1, a scaffolding protein and binding partner of palladin and α-actinin-1, during bacterial infections. We show that PDLIM1 localizes to the site of initial Listeria entry into cells. Following this, PDLIM1 localizes to actin filament clouds surrounding immotile bacteria, and then colocalizes with actin once the comet/rocket tails are generated. Unlike palladin or α-actinin-1, PDLIM1 is maintained within the actin-rich core of membrane protrusions. Conversely, α-actinin-1, but not PDLIM1 (or palladin), is enriched at the membrane invagination that internalizes the Listeria-containing membrane protrusion. We also show that PDLIM1 is a component of the EPEC pedestal core and that its recruitment is dependent on the bacterial effector Tir. Our findings highlight PDLIM1 as another protein present within pathogen-induced actin-rich structures.
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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".