What's wrong with correlative experiments?
ABSTRACT Here, we make a case for multivariate measurements in cell biology with minimal perturbation. We discuss how correlative data can identify cause-effect relationships in cellular pathways with potentially greater accuracy than conventional perturbation studies.
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ABSTRACT: A characteristic feature of motile cells as they undergo a change in motile behavior is the development of fluctuating exploratory motions of the leading edge, driven by actin polymerization. We review quantitative models of these protrusion and retraction phenomena. Theoretical studies have been motivated by advances in experimental and computational methods that allow controlled perturbations, single molecule imaging, and analysis of spatiotemporal correlations in microscopic images. To explain oscillations and waves of the leading edge, most theoretical models propose nonlinear interactions and feedback mechanisms among different components of the actin cytoskeleton system. These mechanisms include curvature-sensing membrane proteins, myosin contraction, and autocatalytic biochemical reaction kinetics. We discuss how the combination of experimental studies with modeling promises to quantify the relative importance of these biochemical and biophysical processes at the leading edge and to evaluate their generality across cell types and extracellular environments.Cytoskeleton 04/2012; 69(4):195-206. DOI:10.1002/cm.21017 · 3.01 Impact Factor
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ABSTRACT: Cellular signal transduction occurs in complex and redundant interaction networks, which are best understood by simultaneously monitoring the activation dynamics of multiple components. Recent advances in biosensor technology have made it possible to visualize and quantify the activation of multiple network nodes in the same living cell. The precision and scope of this approach has been greatly extended by novel computational approaches (referred to as computational multiplexing) that can reveal relationships between network nodes imaged in separate cells.Nature Reviews Molecular Cell Biology 11/2011; 12(11):749-56. DOI:10.1038/nrm3212 · 36.46 Impact Factor
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ABSTRACT: Arguably, one of the foremost distinctions between life and non-living matter is the ability to sense environmental changes and respond appropriately--an ability that is invested in every living cell. Within a single cell, this function is largely carried out by networks of signaling molecules. However, the details of how signaling networks help cells make complicated decisions are still not clear. For instance, how do cells read graded, analog stress signals but convert them into digital live-or-die responses? The answer to such questions may originate from the fact that signaling molecules are not static but dynamic entities, changing in numbers and activity over time and space. In the past two decades, researchers have been able to experimentally monitor signaling dynamics and use mathematical techniques to quantify and abstract general principles of how cells process information. In this review, the authors first introduce and discuss various experimental and computational methodologies that have been used to study signaling dynamics. The authors then discuss the different types of temporal dynamics such as oscillations and bistability that can be exhibited by signaling systems and highlight studies that have investigated such dynamics in physiological settings. Finally, the authors illustrate the role of spatial compartmentalization in regulating cellular responses with examples of second-messenger signaling in cardiac myocytes.Protein Science 07/2012; 21(7):918-28. DOI:10.1002/pro.2089 · 2.86 Impact Factor