RNAi Library Screening Reveals Gβ 1 , Casein Kinase 2α and ICAP-1 as Novel Regulators of LFA-1-mediated T-cell Polarity and Migration
Bibliographic record
Abstract
The α L β 2 integrin LFA-1 plays a key role in T-cell adhesion to the endothelial vasculature and migration into both secondary lymphoid organs and peripheral tissues via interactions with its target protein ICAM-1. Although members of the chemokine family of G-protein coupled receptors and heterotrimeric G proteins are known to influence LFA-1 activation and ICAM binding, the role of these receptors and their downstream effectors has not been fully characterised. In addition, a number of kinases are activated in response to LFA-1/ICAM-1 signalling in T-cells but the extent to which the kinome influences T-cell migration is not fully understood. In this study we screened two RNAi libraries targeting G protein-coupled receptors (GPCR)/GPCR-associated proteins and kinases in a HuT-78 T-cell line model of LFA-1-stimulated T cell migration. Based on staining of the actin cytoskeleton, multiple parameters to measure cell morphology were used to assess the contribution of 1109 genes to LFA-1-mediated T cell polarity and migration. These RNAi screens identified a number of both novel and previously identified genes that either increased or decreased the polarity and migratory capacity of these cells. Following multiparametric analysis, hierarchical clustering and pathway analysis, three of these genes were characterised in further detail using primary human T-cells, revealing novel roles for the heterotrimeric G protein subunit Gβ1 and casein kinase 2 in LFA-1-mediated T-cell polarity and migration in-vitro. Our studies also highlighted a new role for ICAP-1, an adaptor protein previously described to be associated with β1 integrins, in β2 integrin LFA-1-directed migration in T-cells. Knockdown of ICAP-1 expression in primary T cells revealed a role in cell polarity, cell velocity and transmigration towards SDF-1 for this adaptor protein. This study therefore uncovers new roles for GPCR/GPCR-associated proteins and kinases in T-cell migration and provides potential novel targets for modulation of the T-cell immune response.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
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".