Note to users. If you're seeing this message, it means that your browser cannot find this page's style/presentation instructions -- or possibly that you are using a browser that does not support current Web standards. Find out more about why this message is appearing, and what you can do to make your experience of our site the best it can be.

Subscribe

Sci. Signal., 5 June 2012
Vol. 5, Issue 227, p. ec159
[DOI: 10.1126/scisignal.2003286]

EDITORS' CHOICE

Computational Biology Perturbing Behavior to Uncover Polarization Signals

Ernesto Andrianantoandro

Science Signaling, AAAS, Washington, DC 20005, USA

Ku et al. present an approach based on perturbation analysis that infers signal transduction dynamics without a complete biochemical understanding of the network. Polarization of neutrophils in response to chemoattractants is an ideal system for applying this approach. This polarization process involves three "modules" comprising distinct events mediated by spatially restricted effector molecules and their requisite upstream signaling molecules: (i) membrane protrusion driven by actin polymerization, which is regulated by the guanosine triphosphatase (GTPase) Rac2; (ii) cell contraction, which is regulated by activation of myosin light chain 2 (MLC2) and signaling by the GTPase RhoA; and (iii) delivery and storage of polarity components, which is controlled by microtubules. Primary human neutrophils treated with drugs that stabilize or destabilize, or that activate or deactivate the cytoskeletal proteins in each module then stimulated with chemoattractant were fixed and observed at various time points by microscopy. The authors stained for actin filaments, phosphorylated MLC2, or microtubules as readouts for the signaling occurring in each module. Fluorescence intensity served as a gauge for activity of each module, and spatial distribution of fluorescence served as an indicator of polarity. Through computational analysis, the authors visualized how perturbations of one module influenced other modules, showed that the amount of influence changed over time, and used this to construct causal networks connecting the three modules. Identifying links that persisted over time in the causal networks revealed a linear topology underlying signal activity and a feed-forward topology in the opposite direction underlying signal polarity. Some of these links agreed with previously identified interactions, but others were previously uncharacterized, opening the door for future investigation.

C.-J. Ku, Y. Wang, O. D. Weiner, S. J. Altschuler, L. F. Wu, Network crosstalk dynamically changes during neutrophil polarization. Cell 149, 1073–1083 (2012). [Online Journal]

Citation: E. Andrianantoandro, Perturbing Behavior to Uncover Polarization Signals. Sci. Signal. 5, ec159 (2012).



To Advertise     Find Products


Science Signaling. ISSN 1937-9145 (online), 1945-0877 (print). Pre-2008: Science's STKE. ISSN 1525-8882