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      A Logical Model Provides Insights into T Cell Receptor Signaling


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          Cellular decisions are determined by complex molecular interaction networks. Large-scale signaling networks are currently being reconstructed, but the kinetic parameters and quantitative data that would allow for dynamic modeling are still scarce. Therefore, computational studies based upon the structure of these networks are of great interest. Here, a methodology relying on a logical formalism is applied to the functional analysis of the complex signaling network governing the activation of T cells via the T cell receptor, the CD4/CD8 co-receptors, and the accessory signaling receptor CD28. Our large-scale Boolean model, which comprises 94 nodes and 123 interactions and is based upon well-established qualitative knowledge from primary T cells, reveals important structural features (e.g., feedback loops and network-wide dependencies) and recapitulates the global behavior of this network for an array of published data on T cell activation in wild-type and knock-out conditions. More importantly, the model predicted unexpected signaling events after antibody-mediated perturbation of CD28 and after genetic knockout of the kinase Fyn that were subsequently experimentally validated. Finally, we show that the logical model reveals key elements and potential failure modes in network functioning and provides candidates for missing links. In summary, our large-scale logical model for T cell activation proved to be a promising in silico tool, and it inspires immunologists to ask new questions. We think that it holds valuable potential in foreseeing the effects of drugs and network modifications.

          Author Summary

          T-lymphocytes are central regulators of the adaptive immune response, and their inappropriate activation can cause autoimmune diseases or cancer. The understanding of the signaling mechanisms underlying T cell activation is a prerequisite to develop new strategies for pharmacological intervention and disease treatments. However, much of the existing literature on T cell signaling is related to T cell development or to activation processes in transformed T cell lines (e.g., Jurkat), whereas information on non-transformed primary T cells is limited. Here, immunologists and theoreticians have compiled data from the existing literature that stem from analysis of primary T cells. They used this information to establish a qualitative Boolean network that describes T cell activation mechanisms after engagement of the TCR, the CD4/CD8 co-receptors, and CD28. The network comprises 94 nodes and can be extended to facilitate interpretation of new data that emerge from experimental analysis of T cell activation. Newly developed tools and methods allow in silico analysis, and manipulation of the network and can uncover hidden/unforeseen signaling pathways. Indeed, by assessing signaling events controlled by CD28 and the protein tyrosine kinase Fyn, we show that computational analysis of even a qualitative network can provide new and non-obvious signaling pathways which can be validated experimentally.

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          Most cited references 43

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          Robustness, the ability to maintain performance in the face of perturbations and uncertainty, is a long-recognized key property of living systems. Owing to intimate links to cellular complexity, however, its molecular and cellular basis has only recently begun to be understood. Theoretical approaches to complex engineered systems can provide guidelines for investigating cellular robustness because biology and engineering employ a common set of basic mechanisms in different combinations. Robustness may be a key to understanding cellular complexity, elucidating design principles, and fostering closer interactions between experimentation and theory.
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              Discovery of a novel, potent, and Src family-selective tyrosine kinase inhibitor. Study of Lck- and FynT-dependent T cell activation.

              Here, we have studied the activity of a novel protein-tyrosine kinase inhibitor that is selective for the Src family of tyrosine kinases. We have focused our study on the effects of this compound on T cell receptor-induced T cell activation, a process dependent on the activity of the Src kinases Lck and FynT. This compound is a nanomolar inhibitor of Lck and FynT, inhibits anti-CD3-induced protein-tyrosine kinase activity in T cells, demonstrates selectivity for Lck and FynT over ZAP-70, and preferentially inhibits T cell receptor-dependent anti-CD3-induced T cell proliferation over non-T cell receptor-dependent phorbol 12-myristate 13-acetate/interleukin-2 (IL-2)-induced T cell proliferation. Interestingly, this compound selectively inhibits the induction of the IL-2 gene, but not the granulocyte-macrophage colony-stimulating factor or IL-2 receptor genes. This compound offers a useful new tool for examining the role of the Lck and FynT tyrosine kinases versus ZAP-70 in T cell activation as well as the role of other Src family kinases in receptor function.

                Author and article information

                Role: Editor
                PLoS Comput Biol
                PLoS Computational Biology
                Public Library of Science (San Francisco, USA )
                August 2007
                24 August 2007
                5 July 2007
                : 3
                : 8
                [1 ] Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany
                [2 ] Institute of Immunology, Otto-von-Guericke University, Magdeburg, Germany
                [3 ] Institute for Mathematical Optimization, Otto-von-Guericke University, Magdeburg, Germany
                Utrecht University, The Netherlands
                Author notes
                * To whom correspondence should be addressed. E-mail: inquiries regarding the mathematical methodology should be addressed to Steffen Klamt, klamt@ 123456mpi-magdeburg.mpg.de , and regarding the biological and experimental data to Burkhart Schraven, Burkhart.Schraven@ 123456med.ovgu.de
                07-PLCB-RA-0064R3 plcb-03-08-15
                Copyright: © 2007 Saez-Rodriguez et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                Page count
                Pages: 11
                Research Article
                Computational Biology
                Custom metadata
                Saez-Rodriguez J, Simeoni L, Lindquist JA, Hemenway R, Bommhardt U, et al. (2007) A logical model provides insights into T cell receptor signaling. PLoS Comput Biol 3(8): e163. doi: 10.1371/journal.pcbi.0030163

                Quantitative & Systems biology


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