Characterization of CEACAM1 and Lipid Raft Nanoclustering, Association and Structure by dSTORM and homo-FRET Imaging

Driouchi, Amine; Giuliani, Maximilano; Gray-Owen, Scott D.; Yip, Christopher M.

doi:10.1016/j.bpj.2015.11.1143

Cited by 2 publications

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“…Furthermore, through increasing the local concentration of CEACAM1 monomers, clustering is promoted. Thus, the presence of lipid raft regions in the Cell4D models creates a spatial dynamic that matches the known observation of CEACAM1 clusters being primarily monomeric within lipid rafts, and dimeric CEACAM1 being localized in lipid-disordered regions outside of rafts [33].…”

Section: Discussionsupporting

confidence: 71%

Cell4D: a general purpose spatial stochastic simulator for cellular pathways

Chan,

Cromar,

Taj

et al. 2024

BMC Bioinformatics

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Background With the generation of vast compendia of biological datasets, the challenge is how best to interpret ‘omics data alongside biochemical and other small-scale experiments to gain meaningful biological insights. Key to this challenge are computational methods that enable domain-users to generate novel hypotheses that can be used to guide future experiments. Of particular interest are flexible modeling platforms, capable of simulating a diverse range of biological systems with low barriers of adoption to those with limited computational expertise. Results We introduce Cell4D, a spatial-temporal modeling platform combining a robust simulation engine with integrated graphics visualization, a model design editor, and an underlying XML data model capable of capturing a variety of cellular functions. Cell4D provides an interactive visualization mode, allowing intuitive feedback on model behavior and exploration of novel hypotheses, together with a non-graphics mode, compatible with high performance cloud compute solutions, to facilitate generation of statistical data. To demonstrate the flexibility and effectiveness of Cell4D, we investigate the dynamics of CEACAM1 localization in T-cell activation. We confirm the importance of Ca2+ microdomains in activating calmodulin and highlight a key role of activated calmodulin on the surface expression of CEACAM1. We further show how lymphocyte-specific protein tyrosine kinase can help regulate this cell surface expression and exploit spatial modeling features of Cell4D to test the hypothesis that lipid rafts regulate clustering of CEACAM1 to promote trans-binding to neighbouring cells. Conclusions Through demonstrating its ability to test and generate hypotheses, Cell4D represents an effective tool to help integrate knowledge across diverse, large and small-scale datasets.

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Section: Discussionsupporting

confidence: 71%

Cell4D: a general purpose spatial stochastic simulator for cellular pathways

Chan,

Cromar,

Taj

et al. 2024

BMC Bioinformatics

View full text Add to dashboard Cite

show abstract

Section: Discussionsupporting

confidence: 71%

Cell4D: A general purpose spatial stochastic simulator for cellular pathways

Chan,

Cromar,

Taj

et al. 2023

Preprint

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STRUCTURED ABSTRACTMotivationWith the generation of vast compendia of ‘omics datasets, the challenge is how best to interpret these datasets to gain meaningful biological insights. Key to this challenge are computational methods that enable domain-users to generate novel hypotheses that can be used to guide future experiments. Of particular interest are flexible modeling platforms, capable of simulating a diverse range of biological systems with low barriers of adoption to those with limited computational expertise.ResultsWe introduce Cell4D, a spatial-temporal modeling platform combining a robust simulation engine with integrated graphics visualization, a model design editor, and an underlying XML data model capable of capturing a variety of cellular functions. Cell4D provides an interactive visualization mode, allowing intuitive feedback on model behaviour and exploration of novel hypotheses, together with a non-graphics mode, compatible with high performance cloud compute solutions, to facilitate generation of statistical data. To demonstrate the flexibility and effectiveness of Cell4D, we investigate the dynamics of CEACAM1 localization in T-cell activation. We confirm the importance of Ca++microdomains in activating calmodulin and highlight a key role of activated calmodulin on the surface expression of CEACAM1. We further show how lymphocyte-specific protein tyrosine kinase can help regulate this cell surface expression and exploit spatial modeling features of Cell4D to test the hypothesis that lipid rafts regulate clustering of CEACAM1 to promote trans-binding to neighbouring cells. Through demonstrating its ability to test and generate hypotheses, Cell4D represents an effective tool to help interpret complex ‘omics datasets.Availability and Implementationhttps://github.com/ParkinsonLab/cell4dContactjparkin@sickkids.ca

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Characterization of CEACAM1 and Lipid Raft Nanoclustering, Association and Structure by dSTORM and homo-FRET Imaging

Cited by 2 publications

References 0 publications

Cell4D: a general purpose spatial stochastic simulator for cellular pathways

Cell4D: a general purpose spatial stochastic simulator for cellular pathways

Cell4D: A general purpose spatial stochastic simulator for cellular pathways

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