title: The self-limiting dynamics of TGF-β signaling in silico and in vitro, with negative feedback through PPM1A upregulation.
abstract: The TGF-β/Smad signaling system decreases its activity through strong negative regulation. Several molecular mechanisms of negative regulation have been published, but the relative impact of each mechanism on the overall system is unknown. In this work, we used computational and experimental methods to assess multiple negative regulatory effects on Smad signaling in HaCaT cells. Previously reported negative regulatory effects were classified by time-scale: degradation of phosphorylated R-Smad and I-Smad-induced receptor degradation were slow-mode effects, and dephosphorylation of R-Smad was a fast-mode effect. We modeled combinations of these effects, but found no combination capable of explaining the observed dynamics of TGF-β/Smad signaling. We then proposed a negative feedback loop with upregulation of the phosphatase PPM1A. The resulting model was able to explain the dynamics of Smad signaling, under both short and long exposures to TGF-β. Consistent with this model, immuno-blots showed PPM1A levels to be significantly increased within 30 min after TGF-β stimulation. Lastly, our model was able to resolve an apparent contradiction in the published literature, concerning the dynamics of phosphorylated R-Smad degradation. We conclude that the dynamics of Smad negative regulation cannot be explained by the negative regulatory effects that had previously been modeled, and we provide evidence for a new negative feedback loop through PPM1A upregulation. This work shows that tight coupling of computational and experiments approaches can yield improved understanding of complex pathways.
authors.affiliation: Computational and Systems Biology, Singapore-MIT Alliance, Singapore; Mechanobiology Institute, Singapore.
authors.forename: Junjie
authors.initials: J
authors.lastname: Wang
authors.affiliation: Computational and Systems Biology, Singapore-MIT Alliance, Singapore; Mechanobiology Institute, Singapore; Centre for Computational Biology, Duke-NUS Graduate Medical School, Singapore.
authors.forename: Lisa
authors.initials: L
authors.lastname: Tucker-Kellogg
authors.affiliation: NUS Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore.
authors.forename: Inn Chuan
authors.initials: IC
authors.lastname: Ng
authors.affiliation: Department of Physiology, National University of Singapore, Singapore.
authors.forename: Ruirui
authors.initials: R
authors.lastname: Jia
authors.affiliation: NUS Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore; School of Computing, National University of Singapore, Singapore.
authors.forename: P S
authors.initials: PS
authors.lastname: Thiagarajan
authors.affiliation: Computational and Systems Biology, Singapore-MIT Alliance, Singapore; Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.
authors.forename: Jacob K
authors.initials: JK
authors.lastname: White
authors.affiliation: Computational and Systems Biology, Singapore-MIT Alliance, Singapore; Mechanobiology Institute, Singapore; NUS Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore; Department of Physiology, National University of Singapore, Singapore; Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.
authors.forename: Hanry
authors.initials: H
authors.lastname: Yu
mesh_terms: D002460:Cell Line; D019295:Computational Biology; D003198:Computer Simulation; D025461:Feedback, Physiological; D006801:Humans; D066298:In Vitro Techniques; D047908:Intracellular Signaling Peptides and Proteins / Q000378:metabolism; D008962:Models, Theoretical; D010749:Phosphoprotein Phosphatases / Q000378:metabolism*; D010766:Phosphorylation; D000071636:Protein Phosphatase 2C; D059748:Proteolysis; D011518:Proto-Oncogene Proteins / Q000378:metabolism; D015398:Signal Transduction; D051896:Smad Proteins, Receptor-Regulated / Q000378:metabolism; D016212:Transforming Growth Factor beta / Q000378:metabolism*; D015854:Up-Regulation
chemical_list: D047908:Intracellular Signaling Peptides and Proteins; D011518:Proto-Oncogene Proteins; C060615:SKIL protein, human; D051896:Smad Proteins, Receptor-Regulated; D016212:Transforming Growth Factor beta; C000607456:PPM1A protein, human; D010749:Phosphoprotein Phosphatases; D000071636:Protein Phosphatase 2C