ArticlePLoS computational biology2022
Spatially resolved in silico modeling of NKG2D signaling kinetics suggests a key role of NKG2D and Vav1 Co-clustering in generating natural killer cell activation.
Article in PLoS computational biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 9 citations in OpenAlex.
- Next-generation natural killer cell therapy: bench to bedside and beyond.Signal transduction and targeted therapy · 2026Review
- Resting-state spatial statistics of NK cell receptors may improve early signal discrimination.Biophysical journal · 2026Article
- Using In silico models to predict lymphocyte activation and development in a data rich era.Immunoinformatics (Amsterdam, Netherlands) · 2024Article
- PASCAR: a multiscale framework to explore the design space of constitutive and inducible CAR T cells.Life science alliance · 2023Article
- BioNetGMMFit: estimating parameters of a BioNetGen model from time-stamped snapshots of single cells.NPJ systems biology and applications · 2023Article
- Killer instincts: natural killer cells as multifactorial cancer immunotherapy.Frontiers in immunology · 2023Review
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
Natural Killer (NK) cells provide key resistance against viral infections and tumors. A diverse set of activating and inhibitory NK cell receptors (NKRs) interact with cognate ligands presented by target host cells, where integration of dueling signals initiated by the ligand-NKR interactions determines NK cell activation or tolerance. Imaging experiments over decades have shown micron and sub-micron scale spatial clustering of activating and inhibitory NKRs. The mechanistic roles of these clusters in affecting downstream signaling and activation are often unclear. To this end, we developed a predictive in silico framework by combining spatially resolved mechanistic agent based modeling, published TIRF imaging data, and parameter estimation to determine mechanisms by which formation and spatial movements of activating NKG2D microclusters affect early time NKG2D signaling kinetics in a human cell line NKL. We show co-clustering of NKG2D and the guanosine nucleotide exchange factor Vav1 in NKG2D microclusters plays a dominant role over ligand (ULBP3) rebinding in increasing production of phospho-Vav1(pVav1), an activation marker of early NKG2D signaling. The in silico model successfully predicts several scenarios of inhibition of NKG2D signaling and time course of NKG2D spatial clustering over a short (~3 min) interval. Modeling shows the presence of a spatial positive feedback relating formation and centripetal movements of NKG2D microclusters, and pVav1 production offers flexibility towards suppression of activating signals by inhibitory KIR ligands organized in inhomogeneous spatial patterns (e.g., a ring). Our in silico framework marks a major improvement in developing spatiotemporal signaling models with quantitatively estimated model parameters using imaging data.
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