ArticleMethods in enzymology2013
Fluctuation analysis of activity biosensor images for the study of information flow in signaling pathways.
Article in Methods in enzymology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Multiplexed GTPase and GEF biosensor imaging enables network connectivity analysis.Nature chemical biology · 2020Article
- Differential peroxiredoxin hyperoxidation regulates MAP kinase signaling in human articular chondrocytes.Free radical biology & medicine · 2019Article
- Profiling cellular morphodynamics by spatiotemporal spectrum decomposition.PLoS computational biology · 2018Article
- Discovery of functional interactions among actin regulators by analysis of image fluctuations in an unperturbed motile cell system.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2018Review
- Image-based spatiotemporal causality inference for protein signaling networks.Bioinformatics (Oxford, England) · 2017Article
- Combining FRET and optical tweezers to study RhoGTPases spatio-temporal dynamics upon local stimulation.Journal of biological methods · 2017Article
- Coordinated integrin activation by actin-dependent force during T-cell migration.Nature communications · 2016Article
- LOVTRAP: an optogenetic system for photoinduced protein dissociation.Nature methods · 2016Article
- Changes in single-molecule integrin dynamics linked to local cellular behavior.Molecular biology of the cell · 2016Article
- Diagonally Scanned Light-Sheet Microscopy for Fast Volumetric Imaging of Adherent Cells.Biophysical journal · 2016Article
- Oxidative Stress Promotes Peroxiredoxin Hyperoxidation and Attenuates Pro-survival Signaling in Aging Chondrocytes.The Journal of biological chemistry · 2016Article
- Quantitative Multiscale Cell Imaging in Controlled 3D Microenvironments.Developmental cell · 2016Article
- Cysteine-Mediated Redox Regulation of Cell Signaling in Chondrocytes Stimulated With Fibronectin Fragments.Arthritis & rheumatology (Hoboken, N.J.) · 2016Article
- Functional hierarchy of redundant actin assembly factors revealed by fine-grained registration of intrinsic image fluctuations.Cell systems · 2015Article
- ERK reinforces actin polymerization to power persistent edge protrusion during motility.Science signaling · 2015Article
- Subcellular optogenetics - controlling signaling and single-cell behavior.Journal of cell science · 2015Review
- Using fluctuation analysis to establish causal relations between cellular events without experimental perturbation.Biophysical journal · 2014Review
- Automated line scan analysis to quantify biosensor activity at the cell edge.Methods (San Diego, Calif.) · 2014Article
- A RhoC biosensor reveals differences in the activation kinetics of RhoA and RhoC in migrating cells.PloS one · 2013Article
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Authors and funding
7 authors.
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Abstract
Comprehensive understanding of cellular signal transduction requires accurate measurement of the information flow in molecular pathways. In the past, information flow has been inferred primarily from genetic or protein-protein interactions. Although useful for overall signaling, these approaches are limited in that they typically average over populations of cells. Single-cell data of signaling states are emerging, but these data are usually snapshots of a particular time point or limited to averaging over a whole cell. However, many signaling pathways are activated only transiently in specific subcellular regions. Protein activity biosensors allow measurement of the spatiotemporal activation of signaling molecules in living cells. These data contain highly complex, dynamic information that can be parsed out in time and space and compared with other signaling events as well as changes in cell structure and morphology. We describe in this chapter the use of computational tools to correct, extract, and process information from time-lapse images of biosensors. These computational tools allow one to explore the biosensor signals in a multiplexed approach in order to reconstruct the sequence of signaling events and consequently the topology of the underlying pathway. The extraction of this information, dynamics and topology, provides insight into how the inputs of a signaling network are translated into its biochemical or mechanical outputs.
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